DBMS > CrateDB vs. EJDB vs. GigaSpaces

System Properties Comparison CrateDB vs. EJDB vs. GigaSpaces

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Relational DBMS

Graph DBMS
Search engine

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

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Website

cratedb.com

github.com/Softmotions/ejdb

www.gigaspaces.com

Technical documentation

cratedb.com/docs

github.com/Softmotions/ejdb/blob/master/README.md

docs.gigaspaces.com/latest/landing.html

Developer

Crate

Softmotions

Gigaspaces Technologies

Initial release

2013

2012

2000

Current release

5.8.1, August 2024

15.5, September 2020

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2; Commercial licenses available

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

Java, C++, .Net

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

server-less

Linux
macOS
Solaris
Windows

Data scheme

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

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-99 for query and DML statements

APIs and other access methods

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

in-process shared library

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
C++
Java
Python
Scala

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

Triggers

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

none

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

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

Read/Write Locking

yes

Durability

Support for making data persistent

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

Role-based access control

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More resources

Recent citations in the news

CrateDB Appoints Jeff Olson as New CRO
9 July 2024, PR Newswire

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8 April 2024, Datanami

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29 July 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, PR Newswire

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24 October 2023, Cision News

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19 July 2023, CTech

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3 November 2021, PR Newswire

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27 July 2017, DevOps.com

provided by Google News

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