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Infobright DB OverviewUNIXBusinessApplication

What is Infobright DB?

Infobright's high performance analytic database is designed for analyzing large volumes of machine-generated data

Infobright DB is also known as Infobright.

Buyer's Guide

Download the Relational Databases Buyer's Guide including reviews and more. Updated: September 2021

Infobright DB Customers

REZ-1, SonicWALL, IntegriChain, Fuseforward International Inc., Polystar, Live Rail, Mavenir Systems, JDSU Partners, Bango

Infobright DB Video

Archived Infobright DB Reviews (more than two years old)

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it_user708987
MySQL DBA at a financial services firm with 51-200 employees
Real User
Excellent reporting server that is compatible with MySQL

What is our primary use case?

We use Infobright to generate reports for our customers. As their reporting requirements may change over time, it is useful to have a flexible solution such as a columnar-store to be able to answer them.

How has it helped my organization?

Initially, we used a relational database, MySQL along side Hadoop to create summary tables to produce our reports.

Infobright allowed us to reduce the number of moving parts and complexity that we had while providing good performance to produce our reports.

What is most valuable?

Performance, compression, and compatibility with MySQL

What needs improvement?

We ran into some quirks that Infobright had. We interacted with Infobright's support and were able to resolve them.

There still are issues with data replication - Infobright is currently for one server (unless you buy the Infobright appliance). This would mean that redundancy is something you need to implement yourself.

For how long have I used the solution?

Three to five years.

What do I think about the stability of the solution?

I cannot recall too many issues with stability. I would say that it is pretty stable.

What do I think about the scalability of the solution?

It was very good for scalability, even with the limiting factor that it can only be on one machine.

How are customer service and technical support?

Customer Service:

Customer service was very good and very helpful.

Technical Support:

I would rate them highly.

Which solution did I use previously and why did I switch?

We used a relational database, MySQL along side Hadoop. At the time, I believe Hadoop was difficult to rely on and the operation between Hadoop and MySQL were very intensive.

How was the initial setup?

The initial setup was very straightforward.

What about the implementation team?

We implemented it ourselves by following the instructions provided and asked for help from customer service if we ran into a specific issue.

What was our ROI?

Unfortunately, I would not be the right person to ask that. I am aware that Infobright itself was very reasonably priced.

What's my experience with pricing, setup cost, and licensing?

I would advise to test your setup against Infobright and see if it performs well. Have a plan to migrate to it and what that would involve to the best of your knowledge.

Unfortunately, I was insulated from pricing and licensing apart from comments here and there.

Which other solutions did I evaluate?

Yes, we chose Infobright over two other brand name vendors.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
SD
Senior System Architect - Resiliency Engineering at a comms service provider with 10,001+ employees
Real User
If you need a real big data solution, look for a distributed solution that actually has a proven track record.

Pros and Cons

  • "It has very amazing smart grid query feature for very fast aggregate queries across millions of rows"
  • "Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk."

What is our primary use case?

Big data columnar database with steady frequent writes and sporadic reads with high aggregation queries.  Queries would span a few billion rows

What is most valuable?

A valuable feature was the use of a columnar database for large, ever-growing, big datasets.  It also have very amazing smart grid query feature for very fast aggregate queries across millions of rows

How has it helped my organization?

When working properly, the ability to continually insert large datasets, millions of records per minute, while simultaneously querying the same data tables, was very impressive. But it almost never was able to run continually without errors.

What needs improvement?

This version of Infobright has zero support for distributed scalability. The internal smart grid employed for each table has a major flaw in that the data size cannot be expunged until 2GB of data is reached at the column-level.

This is a major flaw, making usage in a big-data scenario impossible. This means that you can delete as many records from a database table as you want. However, unless the 2GB aggregate size threshold was reached for some of the columns in the table, no reduction in disk space usage will occur.

Only the data from the columns that reached 2GB will actually decrease. Other columns below 2GB in size do not leave the disk.

I spent countless hours trying to find some workaround for this. I have nightmares of my e-mail inbox full of unsolvable questions about data size reduction from our field engineers.

What do I think about the stability of the solution?

We experienced major issues with stability. Looking back, this may be because we chose to go with the PostgreSQL version, as opposed to the more tried and true MySQL flavor.

Many stability issues were experienced in the database, reaching error conditions and simply shutting itself down. We actually had calls as frequent as three times a week with Infobright personnel helping them debug their product as they tried to provide hot-fix patches for us.

What do I think about the scalability of the solution?

Scalability was not-existent with this version of Infobright. It existed on one big database server, central-point-of-failure style. We ended up implementing our own sharding client to hash-shard our inbound data to multiple instances of Infobright.

How are customer service and technical support?

The level of technical support was probably about 2/10. While the field rep at Infobright was very enthusiastic, their off-shore developer team was never reachable. I'm not sure they even had any real technical or developer-level staff on the payroll in 2015 and 2016.

Which solution did I use previously and why did I switch?

Infobright database employed as part of a new new Greenfield product we were building. We tried several times to migrate to a different solution.

We were successful in moving a portion of the geographic searchable data into Elastic Search and only use Infobright for storage of the fine-grained data.

How was the initial setup?

The initial setup was always a pain with Infobright's special FTP server which we had to pull the RPM bundles from. We then had to apply a license file.

Eventually, I got it down to about an hour of time that one of my guys would have to burn it in order to install a newly released version.

What about the implementation team?

This was all in-house implementation

What was our ROI?

After all the re-work to our product to remove as much reliance on Infobright, and the extra hardware costs we had to absorb, there was definitely a negative return on investment.

What's my experience with pricing, setup cost, and licensing?

Our pricing was based on server instances and it was actually very cheap compared to Oracle. I guess you get what you pay for.

Which other solutions did I evaluate?

I inherited this product when I came on board. I was told by a well respected "database architect" in the company that this product could handle everything and we were safe to build on top of it.

What other advice do I have?

Do not use the Infobright IEE database. It is a fast, standalone columnar database masquerading as a big data solution. If you need a real big data solution, look for a distributed solution that actually has a proven track record.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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it_user704985
Big Data & Business Intelligence Expert
Vendor
The setting up and running project was much faster than with the alternatives

What is most valuable?

The performance of ad hoc aggregation queries is superior to any RDBMS that I have used and I have used them all.

The parallel load engine (DLP) makes it the fastest load on the market that I know of (as of April 2017.)

The compression of data is also highest on the market anywhere between 10x to 50x, when comparing to raw data.

Valuable Features

  • Ability to support wide and denormalized data sets
  • Small footprint
  • Fast load
  • Ad hoc query capability across denormalized tables
  • Low maintenance costs
  • No need for physical design
  • Low technology footprint
  • Capable of hosting and/or integrating with and analyzing “Big Data”
  • Social Network data
  • Huge volumes
  • Logs of different origins
  • Unstructured and semi-structured data

Short Term Benefits

  • Enhanced Data Relationship Knowledge and Business Rule Design – allows identifying additional detailed BI query needs in a low-cost environment.
  • Mitigate the risk of one shot large builds that do not meet business requirements.
  • Validate schema and evolve the design.
  • Validate and vet detailed requirements and analyze queries before undertaking a costly and lengthy development process.

Long Term Benefits

  • As business conditions change the Sandbox based on IEE allows quick testing and analysis of the impact of these changes.
  • The rapid design, analysis and build cycle, in a DW Discovery Mart, takes one to two weeks versus six to 12 months using traditional data warehousing techniques.
  • Low cost and rapid deployment – easy to maintain with less need for ETL programs, integration logic, and minimal data modeling.

How has it helped my organization?

See answer to the previous question.

What needs improvement?

MPP, distributed processing!!! And better integration with Hadoop.

Additionally, further joins optimization.

For how long have I used the solution?

Since beta version in 2005.

What do I think about the stability of the solution?

No.

What do I think about the scalability of the solution?

No.

How are customer service and technical support?

Dealing with Infobright Inc. - very good and friendly.

Which solution did I use previously and why did I switch?

I used many different databases, Oracle, PostgreSQL, MySQL, Teradata, SQL Server, among others.

With most of them, ad hoc performance, ease of use, no need for physical design and tuning, ability to create extremely large and fast denormalized tables -- those are amongst the most prominent reasons.

Also, small footprint and huge savings with compression was a factor.

The setting up and running project was much faster than with the alternatives. That and relatively low cost would dramatically effect my projects and allow my clients to realize big savings, while getting BI faster to the user and monetizing the information faster, too.

How was the initial setup?

Very fast and straightforward. Faster than any other product. Due to self-tuning and elimination of physical database design, I was able to start full utilization in a matter of minutes.

What's my experience with pricing, setup cost, and licensing?

The price is one of the strongest points of Infobright.

Which other solutions did I evaluate?

As mentioned before, I used many different databases, Oracle, PostgreSQL, MySQL, Teradata, SQL Server and Netezza, among others.

What other advice do I have?

Get the 30-day free trial version and try to implement part of your project or conduct a formal Proof of Concept (PoC). You will be surprised by how easy and fast the development is.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
it_user700143
Computer Engineer at a financial services firm with 201-500 employees
Vendor
In the beginning of the BigData solutions boom, our company had been working with MySQL before, and Infobright gave us the ability to avoid significant changes in our data structure.

What is most valuable?

Ability to work with it in the same manner as MySQL works;

In the beginning of the BigData solutions boom, our company had previously been working with MySQL, and Infobright gave us the ability to avoid significant changes in our data structure and just use Infobright like "BigDataMySql". But there were some disadvantages, too.

How has it helped my organization?

Not improved, it just postponed the required changes, usage of Elasticsearch, Cassandra.

What needs improvement?

It was rather slow, we have had made all reports at night to avoid overload. Any tables modification (except only adding new columns to tables) was prohibited. Even new columns must be added to the end of a table.

For how long have I used the solution?

Around two years.

What do I think about the stability of the solution?

I don't remember something specific, but the server failed to respond on overload and should be restarted.

What do I think about the scalability of the solution?

There was no scalability at all. Infobright didn't permit any changes in tables.

How are customer service and technical support?

I have no information about the technical support.

Which solution did I use previously and why did I switch?

Yes, MySQL. The amount of dataexceeded the limit MySQL (free version) normally works with.

How was the initial setup?

As I remember, it was a special project for the DBA to install and configure Infobright. It was not simple at all.

What's my experience with pricing, setup cost, and licensing?

The price was very high for one server for a startup -- something like $25,000 per year.

Which other solutions did I evaluate?

No, other options required significant code modification.

What other advice do I have?

I don't suggest using an SQL-like solution for Big Data storage at all. But, if this is the case, it should be Oracle or paid versions of MySQL.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
ITCS user
Responsabile Area Progetti BI & SYS at a tech services company with 51-200 employees
Consultant
I love that the solution is a columnar DB.

What is most valuable?

I love that the solution is a columnar DB. This means that there is data compression on the disk, a fully-indexed columnstore, and highly efficient query execution.

How has it helped my organization?

ICE helped us improve the speed for the “group-by” query by 10x. The system is robust and simple (it seems to be MySQL); installation, configuration and backup are very easy. Furthermore, there is no need to fine-tune database schema objects. You can just create the tables and go.

What needs improvement?

Complex subquery and analitycal functions could be improved.

For how long have I used the solution?

We have used this solution for about 5 years.

What do I think about the stability of the solution?

When running a complex subquery, the system hangs without giving the user any response.

What do I think about the scalability of the solution?

I have not encountered any issues with scalability.

How are customer service and technical support?

I used the Community Edition, so there was no support granted.

Which solution did I use previously and why did I switch?

I used row-based proprietary DB for a few years. To meet my goals, however, I switched to this solution. Columnar DB are faster and are simpler than row-based solutions. With Columnar DB, there is no need to create an index, analyze the table/index, tune the structure, etc.

How was the initial setup?

The initial setup very simple. It was just like installing MySQL. Our only task was to implement an effective way to refresh large fact tables, because no delete or trunc partitions are possibile in ICE. So we implemented a method to export all but the window data to refresh, and then to re-import them all.

What's my experience with pricing, setup cost, and licensing?

ICE is a Community Edition product and I test it only on non-production systems. I don’t investigate licensing.

Which other solutions did I evaluate?

No, it was the first columnar DB I tested.

What other advice do I have?

Be carefully with complex query and subquery; ICE does not work with these queries.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
it_user687159
SR Business Intelligence Developer at a tech services company with 11-50 employees
Consultant
We now have multiple times faster queries in comparison to previously.

What is most valuable?

The following features are valuable for us:

  • Columnar type of the database itself.
  • Fast processing.
  • Big data storage.
  • Possibility to use SQL language (MS SSAS uses DAX, MDX).

How has it helped my organization?

We now have multiple times faster queries in comparison to MS SQL.

For how long have I used the solution?

We have been using the solution for six months.

What do I think about the stability of the solution?

We did not encounter any stability issues.

What do I think about the scalability of the solution?

We did not technically have any scalability issues.

How are customer service and technical support?

The technical support is good enough.

Which solution did I use previously and why did I switch?

On the contrary, we have switched back to the MS SSAS Tabular Model, because of pricing policy. The Infobright annual subscription price for one year of usage is more expensive than a full MS SQL Enterprise license.

How was the initial setup?

There were some minor issues. I do not remember what exactly. Technical support gave us all the help we needed.

What's my experience with pricing, setup cost, and licensing?

At the moment when we tried Infobright, the price was high enough especially as it was an annual subscription.

Which other solutions did I evaluate?

We did not evaluate other options before but after. First we tried Infobright, then MS SSAS Tabular Model.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
it_user687174
Dynamic and creative, leading a business consultancy practice in analytics, business Intelligence, crm and strategy. at a tech services company with 1-10 employees
Consultant
It is a game changer in analytics applications.

What is most valuable?

Query, data loading speed, simplicity, reliability, and ease of use are valuable features. Quality of the customer engagement from the Infobright team is also an important factor.

How has it helped my organization?

It has been a major game changer in analytics applications, as the time to market is very short in the data part.

What needs improvement?

There is need for additional DDL functions.

For how long have I used the solution?

I have used this solution for the past six years.

What do I think about the stability of the solution?

We never experienced stability issues.

What do I think about the scalability of the solution?

There were no scalability issues. You need a very small footprint as well as very low HW requirements for the data size and load tasks.

How are customer service and technical support?

The technical support is excellent.

Which solution did I use previously and why did I switch?

It has been our key engine in the columnar database landscape.

How was the initial setup?

The setup process is absolutely straightforward.

What's my experience with pricing, setup cost, and licensing?

The data size per year must be planned to make the best use of it and to choose the appropriate licensing package.

Which other solutions did I evaluate?

We looked at other columnar-based databases such as Vertica Systems.

What other advice do I have?

It is very straightforward and easy to work with. It is excellent for real-time analytics, sensor data and agile data model development/implementation.

Ad-hoc analytics are extremely reliable and easy to live with.

Disclosure: My company has a business relationship with this vendor other than being a customer: We have become partners.
it_user266910
BI Developer at a tech services company with 10,001+ employees
Consultant
For a free product, it has a relatively fast load. However, the Enterprise Edition is too expensive for something that won't replace our Oracle DWH database.

What is most valuable?

The high compression and the relatively fast load for a free product.

For how long have I used the solution?

I used the Community Edition for three years, when I was working for one of my previous employers.

Which solution did I use previously and why did I switch?

We had not used column-oriented database before Infobright.

What about the implementation team?

We implemented this solution via a vendor team but, they didn’t have experience with Infobright before, so basically, they were learning along with us.

What's my experience with pricing, setup cost, and licensing?

We didn’t purchase the Enterprise Edition because it was too expensive for a product that wasn’t going to replace our main DWH database (Oracle),…

What is most valuable?

The high compression and the relatively fast load for a free product.

For how long have I used the solution?

I used the Community Edition for three years, when I was working for one of my previous employers.

Which solution did I use previously and why did I switch?

We had not used column-oriented database before Infobright.

What about the implementation team?

We implemented this solution via a vendor team but, they didn’t have experience with Infobright before, so basically, they were learning along with us.

What's my experience with pricing, setup cost, and licensing?

We didn’t purchase the Enterprise Edition because it was too expensive for a product that wasn’t going to replace our main DWH database (Oracle), but was, somehow, only an addition for it.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
ITCS user
Consultant at a tech consulting company with 51-200 employees
Consultant
Top 20
Column Oriented, Open-Source Analytic Database
Interesting Article about BigData and Column oriented engines written by a student… … Students in major of software engineering are required to take another course named “Data Storage & Information Retrieval Systems” as a prerequisite for Database. DS&IRS mainly focuses on optimized storage and retrieval of data on peripheral storages like a HDD or even Tape! (I did one of my most sophisticated and joyful projects during this course. We had to implement a search engine, which compared to the boolean model of Google, is supposed to be more accurate. More information concerning this project could be found on my older posts). During these courses, student are required to be engaged in specific projects, defined to help students gain a better perspective and intuition of the problem and issue…

Interesting Article about BigData and Column oriented engines written by a student…

… Students in major of software engineering are required to take another course named “Data Storage & Information Retrieval Systems” as a prerequisite for Database. DS&IRS mainly focuses on optimized storage and retrieval of data on peripheral storages like a HDD or even Tape! (I did one of my most sophisticated and joyful projects during this course. We had to implement a search engine, which compared to the boolean model of Google, is supposed to be more accurate. More information concerning this project could be found on my older posts). During these courses, student are required to be engaged in specific projects, defined to help students gain a better perspective and intuition of the problem and issue.

I don’t know about other universities, but in ours, seeing students performances on such projects is such a disappointment. While doing such fun projects as part of your course to learn more, is quite an opportunity, students beg to differ. The whole atmosphere is believing that our professors are torturing us, and we should resist doing any homework or projects! You have no idea how hard it is to manage escaping that dogma, as you have to live among such students. It is unfortunate how most of the students are reluctant to any level of studying. For such students, learning only occurs when they’re faced with a real problem or task.

So here’s the problem. You are supposed to do your internship at a data analysis company. You will be given 100 GBs of data, consisting of 500 millions of records or observations. How would you manage to use that amount of data? If you recall from DS&IR course, you’d know that a single iteration through all the records would take at least 30 minutes, assuming all of your devices are average consumer level. Now imagine you have a typical machine learning optimization problem (a simple unimodal function), that may require at least 100 iterations to converge. Roughly estimated, you’d need at least 50 hours to optimize your function! So what would you do?

That kind of problem has nothing to do with your method of storage, a simple contagious block of data which minimizes seek time on the hard disk, and reading the data in a sequential manner is as best as you can get. Such problems are tackled by using an optimization solution which minimizes access to hard disks and finds a descent optimal solution.

Now imagine you could reduce the amount of data you’d need on each iteration, by selecting records with a specific feature. What would you do? The former problem doesn’t even need a database to perform its job. But now that you need to select some records with a specific attribute (Not necessarily a specific value), you shouldn’t just iterate through the data and test every record against your criteria. You need to manage the data on disk, and create a wise index of the data, which would help you to reduce disk access and answer your problem perfectly (or even close enough). That’s when databases come in handy.

Now the question is, what kind of database should I use? I’m a Macintosh user, with limited ram, a limited and slow hard disk, with a simple processor! Is using Oracle the right choice? The answer is no, you have a specific need and these general purpose databases may not be the logical choice, not to mention the price of such applications. So what kind of service do we require? In a general manner, users may need to update the records, or alter the table’s schema and … . To provide such services, databases need to sacrifice speed, memory and even the processor. Long story short, I found an alternative open source database which was perfect for my need.

The infobright, is an open-source database which is claimed to “provide both speed and efficiency. Coupled with 10:1 average compression”. According to their website the main features (for my use) are:

- Ideal for data volumes up to 50TB - Market-leading data compression (from 10:1 to over 40:1), which drastically reduces I/O (improving query performance) and results in significantly less storage than alternative solutions. - Query and load performance remains constant as the size of the database grows. -Runs on low cost, off-the-shelf hardware.

Even though they don’t offer a native Mac solution, They have a virtual machine running Ubuntu, prepared to use the infobright with. And here’s the best part, even though the virtual machine allocations were pretty low (650 MBs of ram, 1 cpu core), it was actually able to answer my queries in about a second! The same query on a server (Quad Core, 16GBs of ram, running MS SQL Server) took the same amount of time. My query was a simple select, but according to the documents, this is highly optimized for business intelligence and data warehousing queries. I only imported 9 millions of records, and it only consumed 70MBs of my hard disk! Amazing, isn’t it? Having all the 500 millions of data imported would only take 3.5 GBs of my disk!!

The infobright, is mainly an optimized version of MySql server, with an engine called brighthouse. Since its interface is SQL, you can easily use Weka or Matlab to fetch the necessary data from your database and integrate it into your learning process, with minimum amount of code.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
ITCS user
Project Manager at a tech company with 51-200 employees
Vendor
Big Data Chronicles: Infobright as column-based database for analytics system
Last several months I was involved into the task of design and implementation of statistics/analytics system for the game in social network. There are a lot of users at the same time. All of them produce huge amount of events. One of the standards for analytics systems is providing fast queries for the collected data. Logically, I used OLAP cubes to collect all kinds of events needed for our team to analyze. Technically, the best way in our case is using column-based storage. I use Infobright. In our case regular RDBMS (SQL) storage or document-based DB like MongoDB is not enough because of performance. They should be used rather for OLTP, but not for MGD OLAP. From other hand, such cool gun as Hadoop-based solution would be overrun. So, Infobright is exactly the case. It was one of the…

Last several months I was involved into the task of design and implementation of statistics/analytics system for the game in social network. There are a lot of users at the same time. All of them produce huge amount of events. One of the standards for analytics systems is providing fast queries for the collected data. Logically, I used OLAP cubes to collect all kinds of events needed for our team to analyze. Technically, the best way in our case is using column-based storage. I use Infobright. In our case regular RDBMS (SQL) storage or document-based DB like MongoDB is not enough because of performance. They should be used rather for OLTP, but not for MGD OLAP. From other hand, such cool gun as Hadoop-based solution would be overrun. So, Infobright is exactly the case. It was one of the best decisions I made as software architect for last several months:

- As it’s pure OLAP solution, so, I’m able to implement any ETL/Storage/Query scheme;

- As Infobright is column-based storage, all my even very sofisticated queries on even huge recordsets have extremely short execution time;

- As all huge functionality like aggregation/filtering is hidden in Inforbright’s internals, I concentrate on my business task, so, able to desing/implement/add new module/scheme/query very quickly.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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