CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Java

JavaScript

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X

BSD
Linux
OS X
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

predefined scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like SELECT, DML and DDL statements (CQL)

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

HTTP REST

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Supported programming languages

Natural

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

JavaScript

Server-side scripts

Stored procedures

in Natural

user defined functions (Javascript)

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

based on Cassandra

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

based on Cassandra

selectable replication factor

Representation of geographical distribution of servers is possible

Configurable replication on table/partition-level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency
Read-after-write consistency on record level

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomicity and isolation are supported for single operations

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Access rights for users can be defined per object

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

See CrateDB pricing >
» more

News

How Concide Built its Chat Platform with Enhanced Document Management for Legal Tech Professionals
23 May 2024

Astra Vectorize: Generate Vector Embeddings with 1 Line of Code
22 May 2024

GitHub Copilot + DataStax Astra DB: Build GenAI Apps 100x Faster
21 May 2024

Empowering On-Premises Deployments with Generative AI: Introducing Vector Search for a Self-Managed Modern Architecture
15 May 2024

Tips and Tricks for the DataStax Astra CLI
7 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.