DBMS > atoti vs. Badger vs. EJDB vs. IBM Db2 Event Store vs. Oracle Coherence

System Properties Comparison atoti vs. Badger vs. EJDB vs. IBM Db2 Event Store vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Distributed Event Store optimized for Internet of Things use cases

Oracles in-memory data grid solution

Primary database model

Object oriented DBMS

Key-value store

Document store

Event Store
Time Series DBMS

Key-value store

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Website

atoti.io

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

www.ibm.com/products/db2-event-store

www.oracle.com/java/coherence

Technical documentation

docs.atoti.io

godoc.org/github.com/dgraph-io/badger

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

www.ibm.com/docs/en/db2-event-store

docs.oracle.com/en/middleware/standalone/coherence

Developer

ActiveViam

DGraph Labs

Softmotions

IBM

Oracle

Initial release

2017

2012

2017

2007

Current release

2.0

14.1, August 2023

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

Open Source

GPLv2

commercial

free developer edition available

commercial

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

C and C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java VM

Data scheme

schema-free

yes

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.

Secondary indexes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

through the embedded Spark runtime

APIs and other access methods

in-process shared library

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C++
Java

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Active-active shard replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
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

configurable

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Read/Write Locking

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Best use of cloud: ActiveViam
28 November 2023, Risk.net

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, IBM

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

provided by Google News

Create custom Event Compression Policies in Enterprise Manager to reduce event noise
21 September 2023, Oracle

Microservices with Major New Coherence and Helidon Releases
9 August 2022, Oracle

Nike achieves scalability and performance with Oracle Coherence & Exadata
20 December 2012, Oracle

Use your Universal Credits with Oracle WebLogic Server for OKE
15 October 2020, Oracle

Setting Up ODI Marketplace Agents in High Availability with ATP
24 July 2020, Oracle

provided by Google News

Share this page