Get started with Hyper-Converged Database (HCD)

Hyper-Converged Database (HCD) is a powerful tool for managing your data. This topic provides basic information and a roadmap to documentation for users new to HCD.

HCD provides all the capabilities of Apache Cassandra®. In addition, you may optionally choose to set up and use HCD with Vector. Evaluate HCD with Vector free of charge for 180 days. Note that non-production issues raised with DataStax support will incur a charge.

Keep in mind that if you want to have DataStax manage your database, you can use DataStax Astra DB, a cloud-native database-as-a-service built on Cassandra.

Plan your installation

Self-managed clusters require planning to ensure that you have the right hardware and software to support your workload. Explore the following topics to help you plan your cluster:

Choose a deployment method

Before starting development, you need to deploy an HCD cluster. DataStax offers a variety of ways to set up a cluster. Select the method below that best suits your environment.

Method	Description
Mission Control (preferred method)	Mission Control is a cloud-based service that provides a unified management console for your database clusters. If you are planning a production deployment, DataStax recommends using Mission Control to manage your clusters. For installation instructions, see Install and configure Mission Control. Mission Control is also able to deploy the Data API for a simple JSON document oriented interface to data. For more details on the Data API and how it compares to the CQL interface, see API reference overview.
CLI	You can manually run kubectl commands to install HCD. DataStax recommends that you use this installation method only if you have experience with Kubernetes. You can use the Mission Control UI to install HCD without running Kubernetes manually.
Docker	You can use Docker to explore non-prod development with HCD in a containerized environment. An image for HCD is available at https://hub.docker.com/r/datastax/HCD/.

Method

Description

Mission Control (preferred method)

Mission Control is a cloud-based service that provides a unified management console for your database clusters. If you are planning a production deployment, DataStax recommends using Mission Control to manage your clusters. For installation instructions, see Install and configure Mission Control.

Mission Control is also able to deploy the Data API for a simple JSON document oriented interface to data. For more details on the Data API and how it compares to the CQL interface, see API reference overview.

CLI

You can manually run kubectl commands to install HCD. DataStax recommends that you use this installation method only if you have experience with Kubernetes. You can use the Mission Control UI to install HCD without running Kubernetes manually.

Docker

You can use Docker to explore non-prod development with HCD in a containerized environment. An image for HCD is available at https://hub.docker.com/r/datastax/HCD/.

For installation instructions, see Install HCD.

Choose API and connect

HCD 1.0 provides a variety of APIs for developing applications:

API Description

API	Description
Data API with clients	The Data API is DataStax’s newest API for writing applications that store and query unstructured document data. The main development tool for writing applications that use the Data API are the clients that are currently available in three languages: Python, TypeScript, and Java.
CQL API with drivers	The Cassandra Query Language (CQL) is a SQL-like language for querying and managing databases. It stores structured data in tables and uses primary keys to index data. The main development tool for writing applications that use CQL are the community-supported and DataStax-supported drivers that are available in various languages. For example, see Python, NodeJS, or Java quickstarts. For details, see DataStax drivers.
CQL API with `cqlsh`	The Cassandra Query Language Shell (`cqlsh`) is a command-line utility for executing CQL commands. If you are in the development phase and want to quickly test queries, `cqlsh` is a good tool to use. See instructions for using `cqlsh` in Connect with cqlsh. The CQL documentation provides information on all aspects of creating schema and querying data.

Data API with clients

The Data API is DataStax’s newest API for writing applications that store and query unstructured document data. The main development tool for writing applications that use the Data API are the clients that are currently available in three languages: Python, TypeScript, and Java.

CQL API with drivers

The Cassandra Query Language (CQL) is a SQL-like language for querying and managing databases. It stores structured data in tables and uses primary keys to index data. The main development tool for writing applications that use CQL are the community-supported and DataStax-supported drivers that are available in various languages. For example, see Python, NodeJS, or Java quickstarts.

For details, see DataStax drivers.

CQL API with cqlsh

The Cassandra Query Language Shell (cqlsh) is a command-line utility for executing CQL commands. If you are in the development phase and want to quickly test queries, cqlsh is a good tool to use. See instructions for using cqlsh in Connect with cqlsh. The CQL documentation provides information on all aspects of creating schema and querying data.

For details, see Connection methods comparison.

Load data

DataStax provides tools for getting data into and out of the database:

Secure

Use Cassandra’s built-in security features to protect your data from unauthorized access:

HCD includes the default role cassandra with password cassandra. This is a superuser login with full access to the database. DataStax recommends using the cassandra role solely during the initial role-based access control (RBAC) setup to establish your own root account. Afterward, it is advisable to disable the cassandra role. See Adding a superuser role.

Operations

Operations involves all those tasks that are necessary to keep the database running smoothly. Mission Control automates and simplifies these tasks. The most common operations include: