DBMS > CrateDB vs. Graph Engine vs. OpenMLDB

System Properties Comparison CrateDB vs. Graph Engine vs. OpenMLDB

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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

An open-source machine learning database that provides a feature platform for training and inference

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Graph DBMS
Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.67
Rank	#225	Overall
	#37	Document stores
	#5	Spatial DBMS
	#17	Search engines
	#19	Time Series DBMS
	#16	Vector DBMS

Score	0.58
Rank	#239	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.05
Rank	#358	Overall
	#38	Time Series DBMS

Website

cratedb.com

www.graphengine.io

openmldb.ai

Technical documentation

cratedb.com/docs

www.graphengine.io/docs/manual

openmldb.ai/docs/zh/main

Developer

Crate

Microsoft

4 Paradigm Inc.

Initial release

2013

2010

2020

Current release

5.8.1, August 2024

2024-2 February 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

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.

Implementation language

Java

.NET and C

C++, Java, Scala

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

.NET

Linux

Data scheme

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

yes

Fixed schema

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

APIs and other access methods

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

RESTful HTTP API

JDBC
SQLAlchemy

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

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

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

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

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

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