DBMS > CrateDB vs. Graph Engine vs. MongoDB vs. Neo4j vs. TimescaleDB

System Properties Comparison CrateDB vs. Graph Engine vs. MongoDB vs. Neo4j vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

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

Graph DBMS
Key-value store

Document store

Graph DBMS

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

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	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	423.96
Rank	#5	Overall
	#1	Document stores

Score	44.47
Rank	#23	Overall
	#1	Graph DBMS

Score	4.87
Rank	#74	Overall
	#4	Time Series DBMS

Website

Technical documentation

cratedb.com/docs

www.graphengine.io/docs/manual

www.mongodb.com/docs/manual

neo4j.com/docs

docs.timescale.com

Developer

Crate

Microsoft

MongoDB, Inc

Neo4j, Inc.

Timescale

Initial release

2013

2010

2009

2007

2017

Current release

6.0.7, June 2023

5.18.1, March 2024

2.13.0, November 2023

License

Commercial or Open Source

Open Source

MIT License

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

GPL version3, commercial licenses available

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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

Java

.NET and C

C++

Java, Scala

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

.NET

Linux
OS X
Solaris
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

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 and schema-optional

yes

Typing

predefined data types such as float or date

yes

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

yes

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

pluggable indexing subsystem, by default Apache Lucene

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

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++
F#
Visual Basic

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

JavaScript

yes

User defined Procedures and Functions

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

in MongoDB Atlas only

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

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.

yes using Neo4j Fabric

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

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

Causal Clustering using Raft protocol

available in in Enterprise Version only

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graphs

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

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

optional, enabled by default

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

User concepts

Access control

rights management via user accounts

Access rights for users and roles

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

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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Neo4j delivers graph technology that has been battle tested for performance and scale...
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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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Neo4j is the market leader, graph database category creator, and the most widely...
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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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Real-Time Recommendations Master Data Management Identity and Access Management Network...
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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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Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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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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Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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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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GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

This Week in Neo4j: Podcast, RAG, Neo4j Guide, ERP and more
13 April 2024

Neo4j Brings GraphRAG Capabilities for GenAI to Google Cloud
9 April 2024

Neo4j Is Now SOC2 Type 2 Compliant
8 April 2024

This Week in Neo4j: GenAI, Workshop Recordings, Graph Data Science Book and more
6 April 2024

This Week in Neo4j: Vectors, Knowledge Graphs, Clustering, Social Networks and more
30 March 2024

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