What users are saying about

Actian Matrix

3 Ratings

Vertica

19 Ratings

Actian Matrix

3 Ratings
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Score 8.7 out of 101

Vertica

19 Ratings
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Score 7.5 out of 101

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Likelihood to Recommend

Actian Matrix

Actian matrix is not good for small data sets. If you have a limited data pool, or do not plan on having multiple users/clients accessing a data source, stick with a more traditional relational database model - Access for the truly small user base, or a DB2 or Oracle back end if your going to have multiple users, and moderate sized data. Actian is for LARGE data sets (Big Data, in the industry parlance). Millions of rows of data from multiple sources with various down stream systems accessing the database. It is for data analytics of large data groups and intense data mining.
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Vertica

Vertica as a data warehouse to deliver analytics in-house and even to your client base on scale is not rivaled anywhere in the market. Frankly, in my experience it is not even close to equaled. Because it is such a powerful data warehouse, some people attempt to use it as a transactional database. It certainly is not one of those. Individual row inserts are slow and do not perform well. Deletes are a whole other story. RDBMS it is definitely not. OLAP it rocks.
Eva Donaldson profile photo

Pros

  • Handles Various data types from multiple sources.
  • Indexing speed - using the Actian platform as a back end database greatly improved processing time.
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  • Analytical querying due to built in analytical functions that actually perform across TB of data.
  • Ingestion of data. We can send billions of rows to Vertica easily via the WOS system and it is ready for use immediately.
  • Efficient storage of data. What raw is TB of data, once ingested into Vertica only takes up GB of disk space.
  • Management! The management console is intuitive and useful making keeping an eye on your cluster easier than any other product like this I have used.
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Cons

  • Its a new product, there are plenty of bugs to work out with regards to converting special reserve characters that might crop up in data.
  • The Matrix 2 Matrix database port tool needs some ironing out.
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  • Could use some work on better integrating with cloud providers and open source technologies. For AWS you will find an AMI in the marketplace and recently a connector for loading data from S3 directly was created. With last release, integration with Kafka was added that can help.
  • Managing large workloads (concurrent queries) is a bit challenging.
  • Having a way to provide an estimate on the duration for currently executing queries / etc. can be helpful. Vertica provides some counters for the query execution engine that are helpful but some may find confusing.
  • Unloading data over JDBC is very slow. We've had to come up with alternatives based on vsql, etc. Not a very clean, official on how to unload data.
Traian Antonescu profile photo

Usability

Actian Matrix6.0
Based on 1 answer
I wish to give higher rating for the speed and efficiency in handling the queries, but only 6 because of consistent bugs we encounter
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No score
No answers yet
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Support

Actian Matrix8.0
Based on 1 answer
  • Faster initial response
  • Trained professionals
  • Very helpful in resolving issues
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No score
No answers yet
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Implementation

Actian Matrix6.0
Based on 1 answer
Leader failover setup is the toughest and lack of proper documentation is making things tough.
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No score
No answers yet
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Alternatives Considered

Actian Matrix is our first big data analytics storage platform, and as I was not involved in the POC process to compare it to other products out on the market, unfortunately I cannot say if it is better than other Big Data storage options. I can say that it out performs products such as Oracle or UDB in regards to the volume of data it can easily index and handle.
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Vertica is much easier to manage; is just software (i.e. vs. Netezza), easier to scale and extend, with a very powerful query execution engine and storage layer. While other solutions (e.g. Greenplum) are just postgres clones that were extended to run at scale but still keep their traditional database features (e.g. indexes, materialized views, etc), Vertica has been built from scratch with performance in mind. Five years ago Vertica's storage layer was pretty advanced with very few contenders. Currently more are copying it and lately you can find features like RLE (run length encoding), etc., even in open source columnar formats like Parquet, ORC. So in order to keep up, Vertica has been extended with Hadoop, Kafka, unstructured data (FlexTables) support, etc.
Traian Antonescu profile photo

Return on Investment

  • I cannot comment on the specific numbers, all I can say is that switching to the backend greatly improved our processing speed. The more we process through our systems, the more clients we can serve. Which should bump ROI.
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  • Vertica increased our productivity in analyzing the data and validating simple proof of concepts with our data.
  • Results of analytical queries produced from Vertica are used by all departments as well as part of some of our products.
Traian Antonescu profile photo

Pricing Details

Actian Matrix

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Vertica

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details