DBMS > Datomic vs. Firebase Realtime Database vs. Oracle Berkeley DB vs. VelocityDB vs. XTDB

System Properties Comparison Datomic vs. Firebase Realtime Database vs. Oracle Berkeley DB vs. VelocityDB vs. XTDB

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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Widely used in-process key-value store

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Graph DBMS
Object oriented DBMS

Document store

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.datomic.com

firebase.google.com/products/realtime-database

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

velocitydb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.datomic.com

firebase.google.com/docs/database

docs.oracle.com/cd/E17076_05/html/index.html

velocitydb.com/UserGuide

www.xtdb.com/docs

Developer

Cognitect

Google

acquired by Google 2014

Oracle

originally developed by Sleepycat, which was acquired by Oracle

VelocityDB Inc

Juxt Ltd.

Initial release

2012

1994

2011

2019

Current release

1.0.6735, June 2023

18.1.40, May 2020

7.x

1.19, September 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

commercial license available

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

C, Java, C++ (depending on the Berkeley DB edition)

Clojure

Server operating systems

All OS with a Java VM

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Any that supports .NET

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

.Net

HTTP REST
JDBC

Supported programming languages

Clojure
Java

Java
JavaScript
Objective-C

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net

Clojure
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

limited functionality with using 'rules'

Triggers

By using transaction functions

Callbacks are triggered when data changes

yes

only for the SQL API

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

User concepts

Access control

yes, based on authentication and database rules

Based on Windows Authentication

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