DBMS > EJDB vs. Ignite vs. SQream DB vs. WakandaDB

System Properties Comparison EJDB vs. Ignite vs. SQream DB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

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.

a GPU-based, columnar RDBMS for big data analytics workloads

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store

Key-value store
Relational DBMS

Relational DBMS

Object oriented DBMS

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/Softmotions/ejdb

ignite.apache.org

sqream.com

wakanda.github.io

Technical documentation

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

apacheignite.readme.io/docs

docs.sqream.com

wakanda.github.io/doc

Developer

Softmotions

Apache Software Foundation

SQream Technologies

Wakanda SAS

Initial release

2012

2015

2017

2012

Current release

Apache Ignite 2.6

2022.1.6, December 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 2.0

commercial

Open Source

AGPLv3, extended commercial license 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

C++, Java, .Net

C++, CUDA, Haskell, Java, Scala

C++, JavaScript

Server operating systems

server-less

Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

SQL

Support of SQL

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

yes

APIs and other access methods

in-process shared library

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

.Net
JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

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

user defined functions in Python

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

Security Hooks for custom implementations

yes

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More resources

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