Architecture FAQ

DataStax Enterprise’s architecture allows any authorized user to connect to any node in any datacenter and access data using the Cassandra Query Language (CQL 3.4.5 DSE protocol v2). For ease of use, CQL uses a similar syntax to SQL. The most basic way to interact with DataStax Enterprise (DSE) is using the CQL shell, cqlsh. Using cqlsh, you can create keyspaces and tables, insert and query tables, plus much more. Other ways to interact with DSE are:

DataStax Enterprise is a distributed and highly available database that uses peer-to-peer communication. Data modeling in DataStax Enterprise is similar to relational databases while differing in key areas to provide blazingly fast interaction. Relational databases use joins between tables for relationships. DataStax Enterprise uses denormalization to achieve more robust querying.

The NoSQL term originally referred to a new generation of databases that shunned SQL for other interfaces. The term NoSQL has recently become a catch-all term for post-relational "not-only SQL" databases that use a method of storage different from a relational, or SQL, database.

Apache Spark is an open source analytics project that provides a fast and general engine for large-scale data processing. DataStax Enterprise integrates Apache Spark real-time and batch analytics processing to more easily manage both database and analytics with a single operational system.

Apache Solr is an open source search project that produces a highly reliable, scalable, and distributed search system that provides search for databases. DSE Search integrates Solr to manage search indexes with a persistent store. DSE Search provide enterprises with the ability to perform text search and text analysis.

See Migrating data to DataStax Enterprise. You can use the COPY command to read CSV data to DSE and write CSV data from DSE to a file system. The sstableloader provides the ability to bulk load external data into a cluster. However, before moving data to DSE, you need to consider how your client application will query the tables, and do data modeling first. The paradigm shift between relational databases and NoSQL means that a straight move of data from an RDBMS database to DataStax Enterprise will fail. See Migrating data to DataStax Enterprise.

See Planning and testing DataStax Enterprise deployments.

See Planning and testing cluster deployments for hardware requirements. The distributed nature of DataStax Enterprise can actively utilize multiple datacenters across several geographic regions, supporting highly available data under even the most trying circumstances.

You can install DataStax Enterprise in several ways, depending on the purpose of the installation, the type of operating system, and the available permissions. See Which install method should I use?.

The Admin guide and Dev guide provide information about using virtual nodes; setting up security; storing and accessing data exclusively from memory; setting up distributed data replication from remote clusters; running multiple DataStax Enterprise nodes on a single host machine; automating the movement of data across different types of storage media; plus much more.

The Upgrade Guide provides instructions for upgrading DataStax Enterprise. This guide also provides instructions on how to upgrade from Apache Cassandra to DataStax Enterprise.

You can use the same DataStax drivers for DataStax Enterprise, Astra DB, and Apache Cassandra® (OSS). DataStax has unified the DSE and OSS drivers to avoid user confusion and enhance the OSS drivers with some of the features in the DSE drivers. For more information, see the Better Drivers for Cassandra blog.