Good analytical database
May 11, 2021
Good analytical database
Score 9 out of 10
Vetted Review
Verified User
Overall Satisfaction with Vertica
Vertica serves a database niche that is highly ingested with fast query analytics (MPP). It competes with platforms such as Teradata, Greenplum, Exadata, and Netezza. It does not compete with pseudo column stores such as a SQL Server column store, as those types of "features" are immature and still built on an OLTP platform. Vertica is quick with a large amount of data ingestion.
- Column-oriented storage organization, which increases performance of queries.
- Compression, which reduces storage costs and I/O bandwidth. High compression is possible because columns of homogeneous datatypes are stored together and because updates to the main store are batched.
- Shared nothing architecture, which reduces system contention for shared resources and allows gradual degradation of performance in the face of hardware failure.
- Easy to use and maintain through automated data replication, server recovery, query optimization, and storage optimization.
- Support for standard programming interfaces ODBC, JDBC, ADO.NET, and OLEDB.
- Integration to Hadoop with the capability to perform analytics on ORC and Parquet files directly.
- Per TB licensing. Users have to worry about license usage at all times which becomes a challenge with you are working in an organization with huge amounts of data.
- The geospatial functionality could be designed better.
- Support for containerization and flexibility from the deployment standpoint.
- ML libs and it's inbuilt analytical functions.
- Vertica python is a great library for data scientists.
- Vertica is one of the fastest query engines.
- Vertica UDX is one of the best capabilities from which you can extend Vertica based on your custom needs. Its integrated environment for ML models is pretty good which brings analytics on the plate in just a matter of steps.
- Distributed computing, analytics functions and its continuous improvement of the product.
- As far as concurrency is concerned, earlier versions of the platform struggled with concurrency, but enhancements such as cascading resource pools have dramatically improved concurrency and resource management.
Vertica performs well when the query has good stats and is tuned well. Options for GUI clients are ugly and outdated. IO optimized: it's a columnar store with no indexing structures to maintain like traditional databases. The indexing is achieved by storing the data sorted on disk, which itself is run transparently as a background process.
Do you think OpenText Vertica delivers good value for the price?
Yes
Are you happy with OpenText Vertica's feature set?
Yes
Did OpenText Vertica live up to sales and marketing promises?
Yes
Did implementation of OpenText Vertica go as expected?
Yes
Would you buy OpenText Vertica again?
Yes