Kognitio is an ultra-fast SQL engine with a number of different deployment options. Here are some of the most frequently asked questions that we receive from our users.
Yes, if you download and deploy Kognitio on Hadoop, it’s completely free to use with no restrictions on time, scale or functionality.
No, we have one version of Kognitio which comes with full functionality and various deployment options. However the standalone and MapR versions require a software license for use above 512GB RAM.
Kognitio on Hadoop is free and revenue for that comes from customers who wish to take out paid support.
If you deploy Kognitio on standalone servers or on MapR, you will require a software license for use above 512GB RAM.
We offer a range of support options for Kognitio, from web only to full enterprise support. For more information visit our support page.
There are large variations in the performance, flexibility and maturity of available SQL engines.
Hive, Impala and SparkSQL, for example, are new SQL implementations that were developed from scratch for Hadoop. Yet SQL is a very large, complex standard which is difficult enough to implement on a serial platform, but to implement it in parallel is incredibly difficult and time consuming.
For 25 years, Kognitio has been developing parallel SQL. So our SQL engine is much more mature and proven to scale-out for the high concurrency required by business users. Kognitio is also a true in-memory engine.
If you intend to use Kognitio on a Hadoop cluster under YARN, you should install the “on Hadoop” version. Kognitio on Hadoop runs on Hortonworks Data Platform, Cloudera Data Platform, Amazon EMR, Azure HDInsight,
If you intend to use Kognitio on MapR, you should download the MapR version.
If you are not running Hadoop or MapR, then you should install the standalone version of Kognitio.
Whichever deployment option you choose for Kognitio, the product is fundamentally the same. If, for example, you are prototyping in the cloud, anything you create will be fully functional on another Kognitio system that might he running on-premise either on Hadoop, on MapR or as a standalone cluster. This means that you can develop your data model in Kognitio anywhere and be sure it will work on any Kognitio instance you install.
The backup and restore utilities mean it is easy to move objects from one Kognitio instance to another: move a single table or view, a whole schema or a whole system.
Yes, you may need to use some additional drivers or tools which can be found on our All Downloads page. These include extras for running on the different Hadoop distributions, data connectors (e.g. Parquet/ORC) and client tools such as Kognitio’s own GUI for running SQL and monitoring the system.
Kognitio works very well with Tableau and there is a named connector available. We are also technology partners with Qlik and MicroStrategy. We have a beta connector available for Microsoft PowerBI.Kognitio works with any tool that connects to a SQL database using either an ODBC or JDBC connection.
For years we’ve been developing parallel SQL. But historically, the high upfront cost of installing a dedicated hardware infrastructure on which to run Kognitio, meant that it was labelled a niche product. However the emergence of Hadoop has provided us with a ready-made platform for Kognitio’s massively parallel SQL software to run on.
The answer to this depends on your specific use case. If you existing SQL on Hadoop engine is working well for you, then you have no need to change. But if your incumbent platform is forcing you to compromise on the types of analysis you can perform on your data, then it’s not the right platform. Kognitio is the ideal solution where delivery of knowledge needs to be very fast and for hundreds of concurrent users. If you have an idea for a data project that you’re not even attempting to run because you believe the results will arrive far too late, then you should try Kognitio.
Furthermore, Kognitio can be deployed as a YARN application alongside other SQL engines for your specific use cases where the delivery of knowledge needs to be very fast. So it can be a complement to what you already have in place.
There are large variations in the performance, flexibility and maturity of available SQL engines. Hive, Impala and SparkSQL, for example, are new SQL implementations that were developed from scratch for Hadoop.
Yet SQL is a very large, complex standard which is difficult enough to implement on a serial platform, but to implement it in parallel is incredibly difficult and time consuming. For 25 years, Kognitio has been developing parallel SQL so our SQL engine is much more mature and proven to scale-out for the high concurrency required by business users. Kognitio is also a true in-memory engine.
Kognitio has a very flexible way of defining data sources so pretty much any data source can be used, however out of the box we support: - Delimited text files (CSV, TSV etc) - JSON - ORC - Parquet
Kognitio has very rich ANSI standard SQL support, as well as many compatibility functions for Oracle and SQL server syntax.
Although Kognitio is ACID compliant and is capable of doing transaction processing, it is not designed for fast performance as an OLTP (online transaction processing) database. It’s designed for amazing performance on analytical workloads i.e. complex queries over large subsets of data at very high concurrency.
If high throughput single row inserts is your use case, Kognitio is the right solution.
Kognitio’s primary language is SQL. It has extensive SQL capability out-of-the-box. If your analytical requirement is more complex than SQL can support, then additional languages such as Python or R can easily be used.This is done using Kognitio External Scripts where any Linux executable can be accessed from Kognitio using a simple SQL wrapper. This allows complex algorithms to be deployed and made available to BI end-users submitting SQL for standard tools. Read more about External Scripting here
Kognitio nodes run on Linux operating systems which also support a majority of programming/analytical languages. Kognitio’s external scripting sends data to these languages running on each node and then receives the results back into the SQL interface.
Kognitio is designed to be simple to install and administer.
Standalone implementations are very straightforward. Implementations on Hadoop and MapR can require some configuration of the Hadoop/MapR environment of the complexity of the platforms.
Kognitio needs to be installed by someone with access admin rights to the data systems you wish to analyze.
Kognitio can scale both up and out. Increasing data volumes and workloads can be automatically accommodated by small increments in the size of the underlying hardware platform.