DBMS > CrateDB vs. Postgres-XL vs. PouchDB vs. Redis vs. VoltDB

System Properties Comparison CrateDB vs. Postgres-XL vs. PouchDB vs. Redis vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

JavaScript DBMS with an API inspired by CouchDB

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Document store

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

cratedb.com/docs

www.postgres-xl.org/documentation

pouchdb.com/guides

docs.redis.com/latest/index.html
redis.io/docs

docs.voltdb.com

Developer

Crate

Apache Software Foundation

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

VoltDB Inc.

Initial release

2013

2014

since 2012, originally named StormDB

2012

2009

2010

Current release

10 R1, October 2018

7.1.1, June 2019

7.2.5, May 2024

11.3, April 2022

License

Commercial or Open Source

Open Source

Mozilla public license

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

Java

JavaScript

Java, C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
macOS

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

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
OS X

for development

Data scheme

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

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

via views

yes

with RediSearch module

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

distributed, parallel query execution

with RediSQL module

yes

only a subset of SQL 99

APIs and other access methods

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

only for PouchDB Server
JavaScript API

proprietary protocol

RESP - REdis Serialization Protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined functions

View functions in JavaScript

Lua; Redis Functions coming in Redis 7 (slides and Github)

Java

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Eventual Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

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

MVCC

Atomic execution of command blocks and scripts and optimistic locking

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

rights management via user accounts

fine grained access rights according to SQL-standard

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

Users and roles with access to stored procedures

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.