What users are saying about

Actian Matrix

3 Ratings

Amazon Redshift

86 Ratings

Actian Matrix

3 Ratings
Score 8.6 out of 101

Amazon Redshift

86 Ratings
Score 8.4 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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Amazon Redshift

It's the best option when we need to have a high volume of structured data analytics datawarehouse design & development. It perfectly reports fast with tableau reporting tool, even data around 300 million records. It's best suited where the organization is planning to build a custom datawarehouse rather than using any pre-packaged BI Apps data model.
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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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  • Fast analytical queries. The shared nothing and column oriented architecture makes querying very quick compared to databases like Oracle that are designed for OLTP. Scaling is a synch since you can scale out by adding more nodes.
  • Easy table modelling. The only tough decisions you have to make are what your distribution schemes and sort keys are going to be. This is a lot easier than defining partition and index schemes in databases like Oracle or MySQL.
  • Not much maintenance. Almost everything is managed by Amazon. The only exception is table vacuuming and analysis. I was able to program simple ETL jobs to perform this.
  • Works with pretty much anything that works with Postgres. It's hard to find a tool that it isn't compatible with.
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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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  • Lack of enforced constraints (except NOT NULL column constraints). You have to be very careful in your testing to make sure that you aren't duplicating rows.
  • No stored procedure support. Everything must be accomplished through ETL
  • Write operations are very slow and complex.Native SQL row level INSERT and UPDATE statements take an extremely long time to execute. In order to get around this for external data that needs to be loaded, you have to bulk load the data from a flat file to a stage table, then upsert the data from the stage table to your destination table. For data already present in the database, ELT is the only viable way of transforming the data.
  • No good native data modelling tools.
  • Random nondescript errors happen occasionally. The error messages are not decipherable and forums will have no clues as to what happened. It is just a fact of life.
  • No trigger support.
  • OLTP style queries are painfully slow. Don't even think about using Redshift for OLTP...
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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
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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
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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
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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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Than Vertica: Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS).
Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again.
Than Hive: Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.
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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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  • Allowed us to easily analyze business operations and facilitate A/B testing.
  • Allowed us to quickly answer complex questions about the company's data.
  • Took a lot of work to fix some issues once we got to the limits of its usability (specifically, we had too many writes).
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Pricing Details

Actian Matrix

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

Amazon Redshift

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