Databricks Previous Solutions
JH
JurajHrapko
Solution Architect at a insurance company with 10,001+ employees
We previously used Azure's data lake product and possibly some Hortonworks.
View full review »I previously used Cloud-Bricks.
Azure Stream Analytics is easy to use and easy to deploy. It's a little bit better. Databricks is still having some stability issues. Azure Stream Analytics has a few input and output sources, and it's scalable to all types of third party or interfaces.
View full review »Buyer's Guide
Databricks
April 2024
Learn what your peers think about Databricks. Get advice and tips from experienced pros sharing their opinions. Updated: April 2024.
767,667 professionals have used our research since 2012.
We are using Dataiku for one project and also SageMaker. We have some issues with scalability using SageMaker, which is why we may be going back to Databricks.
SageMaker is a very specific AI tool.
View full review »AO
Alphonse Okossi
Lead Data Scientist at a manufacturing company with 10,001+ employees
We previously used H2O.
View full review »We did not use another similar solution prior to Databricks.
View full review »I personally prefer using Databricks. However, we also considered using Snowflake, but the pricing was different. It's price per query.
So, as per your storage, a data scientist or a data analytics team needs to query again and again, which does not suit a data-heavy organization.
View full review »I previously used HD Insight from Microsoft, but it took many, many hours to process data, so we switched to Databricks.
View full review »Prior to Databricks, we initially used Hadoop. Afterwards, we used HANA, SAP HANA, and the Microsoft SQL Server.
View full review »RC
RameshCh
Sr. BigData Architect at ITC Infotech
We work with multiple clients and this solution is just one of the examples of products we work with. We use several others as well, depending on the client.
It's all wrappers between the same underlying systems. For example, Spark. It's all open-source. We've worked with them as well as the wrappers around it, whether the company was labeled Databrary, IBM insights, Cloudera, etc. These wrappers are all on the same open-source system.
If we with Azure data, we take over Databricks. Otherwise, we have to create a VM separately. Those things are not needed because Azure is already providing those things for us.
I have previously worked with Apache Hadoop, and Databricks is definitely a better product. It's much easier to get data quickly in Databricks. As a result, a lot of the drudgery is taken away. Whereas with Hadoop, it's a bit more tricky to get data together.
View full review »AB
Alexis Bustamante
STI Data Leader at grupo gtd
We are also aware of KNIME, Azure Machine Learning, and Anaconda. In Anaconda, we use many frameworks, for example.
We started with other platforms, like Azure Machine Learning due to the fact that, with AutoML, it's easy to use. However, now that we have more skills, we need other tools or platforms like Databricks. It's a good platform to deploy and develop machine learning in employees.
View full review »I have used Alteryx before. We switched to Databricks because it can compute and turn your code into production-ready code in very few seconds. Also, the stability is relatively high.
GR
reviewer1510053
Head of Referential and Big Data at a financial services firm with 5,001-10,000 employees
We used Cloudera before switching to Databricks.
View full review »RC
reviewer2058633
Data Engineering Manager at a pharma/biotech company with 10,001+ employees
We were using the looped EMR elastic MapReduce from AWS before using Databricks. We switched to Databricks because the whole platform changed from AWS to Azure platform, and Databricks comes as a package.
RX
reviewer1702092
Machine Learning Engineer at a mining and metals company with 10,001+ employees
We have used a lot of different solutions, such as Watson and DataIQ.
View full review »I work with Databricks, Cloudera and Snowflake.
View full review »Prior to using Databricks, we used Azure Stream Analytics. We made the switch because of the scalability and integrated platform.
View full review »AJ
reviewer2046045
Lead Analytics at a manufacturing company with 10,001+ employees
I have not used a similar solution to Databricks.
View full review »AK
Allan Kirszberg
Coordenador Financeiro at Icatu
As we are talking about a corporate solution, the deployment of Databricks lasted longer than the one day it took for Alteryx.
We used Alteryx prior to Databricks and continue to do so, it being the only other solution we have employed. We use the two with different software.
Previously I used Hive and Livy in Zeppelin on an in-house Hadoop installation. The queries constantly threw exceptions and timeouts and the necessary configuration changes proved time-consuming and problematic. Databricks, on the other hand, simply made all those problems vanish.
View full review »I have not worked with another solution prior to Databricks.
View full review »AM
Ariful Mondal
Global Data Architecture and Data Science Director at FH
I have not used tools that are similar to Databricks for workload management, but Azure ADFv2, Google BigQuery, SAS are some the most powerful tools in this space, that I have used in the past. I have also heard of Dataiku and other tools but I have not used them. The only things that I have used are tools written in Python or scripting languages.
View full review »MM
reviewer1558740
Lead Data Architect at a government with 1,001-5,000 employees
I am an IT Consultant and in the past have used different solutions for ETL on top of databases, particularly if we are talking about data warehousing. However, in the last 6 years I have seen large client using a mixture of open source and proprietory technologies, like Informatica stack with data lake in AWS, or Kafka Confluence with MQ Series on top of mainframes and data lake in AWS, Databricks and Azure data lake, etc.
View full review »YK
Yuval Klein
Pre-sale Leader, Big Data Enterprise Solutions at Ness Technologies
I have used Snowflake and one of the differences is that Snowflake is much easier to deploy.
View full review »OB
reviewer1438992
Cloud & Infra Security, Group Manager at a tech vendor with 10,001+ employees
I have used different Microsoft solutions before.
View full review »We previously used the earlier version of Azure Machine Learning services and we decided to move over because over time it became more difficult to deploy. That was two years ago, but now with the new version, it's much easier to deploy Machine Learning.
View full review »We previously used Microsoft stacks. We chose Databricks because the processing power was better and it was a better fit for our use case.
View full review »SH
ShrikanthHebbar
Data Science Consultant at Syniti
Before using Databricks, we were running our own cluster with a web server that executed our Python queries.
View full review »DW
reviewer1235523
Machine Learning Engineer at a tech vendor with 51-200 employees
We didn't previously use a different solution, however, we built our own from scratch. This is the first unified platform that we've used.
View full review »Buyer's Guide
Databricks
April 2024
Learn what your peers think about Databricks. Get advice and tips from experienced pros sharing their opinions. Updated: April 2024.
767,667 professionals have used our research since 2012.