DBMS > AgensGraph vs. GigaSpaces vs. Oracle Berkeley DB vs. SQLite vs. VelocityDB

System Properties Comparison AgensGraph vs. GigaSpaces vs. Oracle Berkeley DB vs. SQLite vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Widely used in-process key-value store

Widely used embeddable, in-process RDBMS

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

Primary database model

Graph DBMS
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Relational DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

bitnine.net/agensgraph

www.gigaspaces.com

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

www.sqlite.org

velocitydb.com

Technical documentation

bitnine.net/documentation

docs.gigaspaces.com/latest/landing.html

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

www.sqlite.org/docs.html

velocitydb.com/UserGuide

Developer

Bitnine Global Inc.

Gigaspaces Technologies

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Dwayne Richard Hipp

VelocityDB Inc

Initial release

2016

2000

1994

2000

2011

Current release

2.1, December 2018

15.5, September 2020

18.1.40, May 2020

3.46.0 (23 May 2024), May 2024

7.x

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

commercial license available

Open Source

Public Domain

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++, .Net

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

Server operating systems

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

server-less

Any that supports .NET

Data scheme

depending on used data model

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

XML can be used for describing objects metadata

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

yes

SQL interfaced based on SQLite is available

yes

SQL-92 is not fully supported

APIs and other access methods

Cypher Query Language
JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

.Net

Supported programming languages

C
Java
JavaScript
Python

.Net
C++
Java
Python
Scala

.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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net

Server-side scripts

Stored procedures

yes

Triggers

yes, event driven architecture

yes

only for the SQL API

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

fine grained access rights according to SQL-standard

Role-based access control

Based on Windows Authentication

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