DBMS > Datomic vs. EJDB vs. Elasticsearch vs. PouchDB vs. TimesTen

System Properties Comparison Datomic vs. EJDB vs. Elasticsearch vs. PouchDB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

JavaScript DBMS with an API inspired by CouchDB

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.datomic.com

github.com/Softmotions/ejdb

www.elastic.co/elasticsearch

pouchdb.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.datomic.com

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

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

pouchdb.com/guides

docs.oracle.com/database/timesten-18.1

Developer

Cognitect

Softmotions

Elastic

Apache Software Foundation

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2010

2012

1998

Current release

1.0.6735, June 2023

8.6, January 2023

7.1.1, June 2019

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

limited edition free

Open Source

GPLv2

Open Source

Elastic License

Open Source

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, Clojure

Java

JavaScript

Server operating systems

All OS with a Java VM

server-less

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

via views

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

in-process shared library

Java API
RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Clojure
Java

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

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

JavaScript

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

View functions in JavaScript

PL/SQL

Triggers

By using transaction functions

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

recommended only for testing and development

Memcached and Redis integration

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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