DBMS > AlaSQL vs. Blazegraph vs. Datomic vs. Drizzle vs. Oracle Berkeley DB

System Properties Comparison AlaSQL vs. Blazegraph vs. Datomic vs. Drizzle vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

JavaScript DBMS library

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Widely used in-process key-value store

Primary database model

Document store
Relational DBMS

Graph DBMS
RDF store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

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

Website

alasql.org

blazegraph.com

www.datomic.com

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

Technical documentation

github.com/AlaSQL/alasql

wiki.blazegraph.com

docs.datomic.com

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

Developer

Andrey Gershun & Mathias R. Wulff

Blazegraph

Cognitect

Drizzle project, originally started by Brian Aker

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2014

2006

2012

2008

1994

Current release

2.1.5, March 2019

1.0.6735, June 2023

7.2.4, September 2012

18.1.40, May 2020

License

Commercial or Open Source

Open Source

MIT-License

Open Source

extended commercial license available

commercial

limited edition free

Open Source

GNU GPL

Open Source

commercial license available

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

JavaScript

Java

Java, Clojure

C++

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

Server operating systems

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

Linux
OS X
Windows

All OS with a Java VM

FreeBSD
Linux
OS X

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SPARQL is used as query language

yes

with proprietary extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JavaScript API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

RESTful HTTP API

JDBC

Supported programming languages

JavaScript

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Clojure
Java

C
C++
Java
PHP

.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

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

yes

By using transaction functions

hooks for callbacks inside the server can be used.

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

But extensive use of caching in the application peers

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

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

yes

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

Security and Authentication via Web Application Container (Tomcat, Jetty)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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