The HCL Actian Data Platform (formerly Actian Avalanche) hybrid cloud data warehouse is a fully managed service that aims to deliver high performance and scale across all dimensions – data volume, concurrent user, and query complexity – at a lower cost than alternative solutions. Avalanche has built-in self-service data integration that can be deployed on-premises as well as on multiple clouds, including AWS, Azure, and Google Cloud, enabling users to migrate or offload applications and data to…
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OpenText Vertica
Score 9.4 out of 10
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The Vertica Analytics Platform supplies enterprise data warehouses with big data analytics capabilities and modernization. Vertica is owned and supported by OpenText.
VectorWise is suitable to be a departmental data mart database or an operational data store (ODS). It is not suitable for enterprise data warehouse database.
As someone just starting out with data analytics and warehousing vertica is a great tool for a small scale business. It has amazing performance and can scale upto TBs of data. It works well for any organization which has about 100 - 500 DAUs of the system. The system doesn't require a lot of ops overhead. Scaling for PB data and 1000s of DAU is vertica's weak point. The system is just not designed for large scale usage and still has a long way to go to improve scalability. There are experiments to run Vertica query engine on top of HDFS which seem promising, however - if you have the the Hadoop ecosystem you are better off going the HDFS + Presto/Impala/SparkSQL route. But if you are in the Hadoop ecosystem, you probably are already investing a lot in ops.
The support community was not as robust as you would find in a Mulesoft or Informatica environment. Given time and growth, it’s possible it will blossom, but for now it is minimal.
Training is always a big thing for us, and the tool was not expansive enough for us to implement our own internal training program. There was some online training, and we acquired an expert when we brought on the new company, but some additional training tools would have helped the tool grown its user base internally.
Not a lot to set it apart from the competition. Most of the features are available with other more established tools, but for a small company that maybe grew too quickly and needs to get its arms around many different data sources, I can see the appeal. Not really geared for larger firms.
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.
As I said before, more training or greater visibility to training tools/options would be a plus. It’s easy to publish YouTube videos these days, I think they should make more of them.
Differentiation would help, there’s not a lot out there to drive you to buy the product if you are well informed in the market. If you know the market, you steer towards the large or trendy products. It’s a good product, but lost in the noise of the field I think.
Hitching the wagon to a major software brand (like Mule did to Salesforce) would help grow the user base, and thus increase the activity in the support community. More users also translates into product champions.
One time, one of the nodes wasn't coming up because of some ambiguity with the local data. Vertica wasn't able to fix it by itself and we were trying to remove the node out of the database and we couldn't do it. It would be great if that could be addressed. Luckily when we rebooted the whole server, some of the dead transaction got flushed because of which vertica was able to recover and the node came up.
HP/Micro Focus Vertica support is in par with other bigger vendors. In addition to this, there is enough best practices documentation available for some of the most common ways you will use Vertica that makes it easy to get Vertica up and running.
We didn’t actually choose Actian, it arrived as part of an acquisition, and really served its purpose both when it was used by the smaller firm we acquired as well as afterwards when we were extracting data and folding the company into our own data and analytics culture. The included hundreds of pre-built connectors gave us lots of options, but in the end, we were just too large of a company to rely on the product and needed a big-name player to address our wide-ranging needs. Powerful for its size, but not sized enough to address big businesses.
MySQL and MS SQL Server are both fantastic RDBMS products. MS SQL Server goes a bit further since it has the builtin analytical functions. But it only scales so far. Once the data goes beyond capacity, getting results out just does not happen anymore. IBM Netezza and Teradata were both appliances that required different expertise than we had in house. Vertica was able to do the same, and in some cases better, on commodity hardware (frankly in our case old servers that were slated for recycling!) and at a small scale. In other words, Vertica we could grow slowly over time. Infobright is a great log processing database but for the functions we were looking to serve it just didn't have some of the features Vertica had that we felt were show stoppers.
