DBMS > Apache Impala vs. EJDB vs. Ignite vs. MySQL vs. ObjectBox

System Properties Comparison Apache Impala vs. EJDB vs. Ignite vs. MySQL vs. ObjectBox

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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.

Widely used open source RDBMS

Extremely fast embedded database for small devices, IoT and Mobile

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Object oriented DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Time Series DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Website

impala.apache.org

github.com/Softmotions/ejdb

ignite.apache.org

www.mysql.com

objectbox.io

Technical documentation

impala.apache.org/impala-docs.html

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

apacheignite.readme.io/docs

dev.mysql.com/doc

docs.objectbox.io

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Softmotions

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

ObjectBox Limited

Initial release

2013

2012

2015

1995

2017

Current release

4.1.0, June 2022

Apache Ignite 2.6

8.3.0, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Java, .Net

C and C++

Server operating systems

Linux

server-less

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Android
iOS
Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

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

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

in-process shared library

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

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary native API

Supported programming languages

All languages supporting JDBC/ODBC

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

C#
C++
Java
PHP
Python
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

yes

proprietary syntax

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes (replicated cache)

Multi-source replication
Source-replica replication

online/offline synchronization between client and server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

not for MyISAM storage engine

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

table locks or row locks depending on storage engine

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Security Hooks for custom implementations

Users with fine-grained authorization concept

no user groups or roles

yes

More information provided by the system vendor

News

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

Vector Database Release for Flutter / Dart + Python
13 June 2023

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