DBMS > Datomic vs. Dragonfly vs. EJDB vs. H2 vs. Lovefield

System Properties Comparison Datomic vs. Dragonfly vs. EJDB vs. H2 vs. Lovefield

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Website

www.datomic.com

github.com/dragonflydb/dragonfly
www.dragonflydb.io

github.com/Softmotions/ejdb

www.h2database.com

google.github.io/lovefield

Technical documentation

docs.datomic.com

www.dragonflydb.io/docs

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

www.h2database.com/html/main.html

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Cognitect

DragonflyDB team and community contributors

Softmotions

Thomas Mueller

Google

Initial release

2012

2023

2012

2005

2014

Current release

1.0.7180, July 2024

1.0, March 2023

2.2.220, July 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSL 1.1

Open Source

GPLv2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

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

C++

Java

JavaScript

Server operating systems

All OS with a Java VM

Linux

server-less

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

in-process shared library

JDBC
ODBC

Supported programming languages

Clojure
Java

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

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

Java

JavaScript

Server-side scripts

Stored procedures

yes

Transaction Functions

Lua

Java Stored Procedures and User-Defined Functions

Triggers

By using transaction functions

publish/subscribe channels provide some trigger functionality

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

none

With clustering: 2 database servers on different computers operate on identical copies of a database

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

yes

using MemoryDB

User concepts

Access control

Password-based authentication

fine grained access rights according to SQL-standard

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