DBMS > CrateDB vs. Ignite vs. MongoDB vs. Redis vs. TimescaleDB

System Properties Comparison CrateDB vs. Ignite vs. MongoDB vs. Redis vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

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.

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Key-value store
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

Time Series DBMS

Secondary database models

Relational DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Relational DBMS

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

Score	0.73
Rank	#229	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	156.44
Rank	#6	Overall
	#1	Key-value stores

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

Technical documentation

cratedb.com/docs

apacheignite.readme.io/docs

www.mongodb.com/docs/manual

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

docs.timescale.com

Developer

Crate

Apache Software Foundation

MongoDB, Inc

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Timescale

Initial release

2013

2015

2009

2017

Current release

Apache Ignite 2.6

6.0.7, June 2023

7.2.4, January 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

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

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

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

Implementation language

Java

C++, Java, .Net

C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
OS X
Windows

Data scheme

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

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

partial

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

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

ANSI-99 for query and DML statements, subset of DDL

Read-only SQL queries via the MongoDB Atlas SQL Interface

with RediSQL module

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

proprietary protocol

RESP - REdis Serialization Protocol

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

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

C#
C++
Java
PHP
Python
Ruby
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes (compute grid and cache interceptors can be used instead)

JavaScript

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

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes (cache interceptors and events)

yes

in MongoDB Atlas only

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

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

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes (replicated cache)

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

can be individually decided for each read operation
Immediate Consistency

default behaviour

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

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

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

Multi-document ACID Transactions with snapshot isolation

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

rights management via user accounts

Security Hooks for custom implementations

Access rights for users and roles

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

See CrateDB pricing >
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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