We performed a comparison between Cassandra and Vertica based on real PeerSpot user reviews.
Find out in this report how the two NoSQL Databases solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."I am satisfied with the performance."
"The time series data was one of the best features along with auto publishing."
"Our primary use case for the solution is testing."
"We can add almost one million columns to the solution."
"The most valuable feature of Cassandra is its fast retrieval. Additionally, the solution can handle large amounts of data. It is the quickest application we use."
"The most valuable features of this solution are its speed and distributed nature."
"Cassandra has some features that are more useful for specific use cases where you have time series where you have huge amounts of writes. That should be quick, but not specifically the reads. We needed to have quicker reads and writes and this is why we are using Cassandra right now."
"I am getting much better performance than relational databases."
"The product's initial setup phase is extremely simple."
"Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data."
"Allows us to take volumes and process them at a very high speed."
"The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful."
"Its projections and encoding are excellent tools for tuning large volumes."
"Vertica is a columnar database, this support our developments in analytics, advanced analytics, and ETL process with large sets of data."
"Initiate on one node, and the RPM propagates automatically to all other nodes. "
"It's the fastest database I have ever tested. That's the most important feature of Vertica."
"Cassandra can improve by adding more built-in tools. For example, if you want to do some maintenance activities in the cluster, we have to depend on third-party tools. Having these tools build-in would be e benefit."
"The solution is not easy to use because it is a big database and you have to learn the interface. This is the case though in most of these solutions."
"The solution is limited to a linear performance."
"Maybe they can improve their performance in data fetching from a high volume of data sets."
"Cassandra could be more user-friendly like MongoDB."
"The secondary index in Cassandra was a bit problematic and could be improved."
"Fine-tuning was a bit of a challenge."
"The solution doesn't have joins between tables so you need other tools for that."
"The integration with AI has room for improvement."
"It would be great if this were a managed service in AWS."
"The biggest problem is the cost of cloud deployment."
"When it is about to reach the maximum storage capacity, it becomes slow."
"It needs integration with multiple clouds."
"There are a lot of limitations within this product and it makes things extremely hard for developers. It lacks Stored Procedure, packages, and triggers like other RDBMs."
"It should provide a GUI interface for data management and tuning."
"Fact-to-fact joins on multi-billion record tables perform poorly."
Cassandra is ranked 4th in NoSQL Databases with 19 reviews while Vertica is ranked 4th in Data Warehouse with 83 reviews. Cassandra is rated 8.0, while Vertica is rated 8.2. The top reviewer of Cassandra writes "Well-equipped to handle a massive influx of data and billions of requests". On the other hand, the top reviewer of Vertica writes " A user-friendly tool that needs to improve its documentation part". Cassandra is most compared with Couchbase, InfluxDB, MongoDB, ScyllaDB and Chroma, whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift and Teradata. See our Cassandra vs. Vertica report.
See our list of best NoSQL Databases vendors.
We monitor all NoSQL Databases reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
SQreamDB is a GPU DB. It is not suitable for real-time oltp of course.
Cassandra is best suited for OLTP database use cases, when you need a scalable database (instead of SQL server, Postgres)
SQream is a GPU database suited for OLAP purposes. It's the best suite for a very large data warehouse, very large queries needed mass parallel activity since GPU is great in massive parallel workload.
Also, SQream is quite cheap since we need only one server with a GPU card, the best GPU card the better since we will have more CPU activity. It's only for a very big data warehouse, not for small ones.
Your best DB for 40+ TB is Apache Spark, Drill and the Hadoop stack, in the cloud.
Use the public cloud provider's elastic store (S3, Azure BLOB, google drive) and then stand up Apache Spark on a cluster sized to run your queries within 20 minutes. Based on my experience (Azure BLOB store, Databricks, PySpark) you may need around 500 32GB nodes for reading 40 TB of data.
Costs can be contained by running your own clusters but Databricks manage clusters for you.
I would recommend optimizing your 40TB data store into the Databricks delta format after an initial parse.
Morten, the most popular comparisons of SQream can be found here: www.itcentralstation.com
The top ones include Cassandra, MemSQL, MongoDB, and Vertica.