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

Python

Java

Server operating systems

Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

server-less

Data scheme

schema-free

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

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

SQL-92 is not fully supported

APIs and other access methods

CLI Client
RESTful HTTP API

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

TinkerPop 3

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Groovy
Java

Server-side scripts

Stored procedures

user defined functions (Javascript)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Configurable replication on table/partition-level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

optional

In-memory capabilities

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

yes

User concepts

Access control

yes

rights management via user accounts

More information provided by the system vendor

Specific characteristics

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

Competitive advantages

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

Typical application scenarios

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

Key customers

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

Market metrics

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

Licensing and pricing models

See CrateDB pricing >
» more

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.