DBMS > GraphDB vs. LokiJS vs. VoltDB vs. XTDB

System Properties Comparison GraphDB vs. LokiJS vs. VoltDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

In-memory JavaScript DBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

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

Primary database model

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

Score	2.76
Rank	#99	Overall
	#8	Graph DBMS
	#4	RDF stores

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.ontotext.com

github.com/techfort/LokiJS

www.voltdb.com

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

Technical documentation

graphdb.ontotext.com/documentation

techfort.github.io/LokiJS

docs.voltdb.com

www.xtdb.com/docs

Social network pages

Developer

Ontotext

VoltDB Inc.

Juxt Ltd.

Initial release

2000

2014

2010

2019

Current release

10.4, October 2023

11.3, April 2022

1.19, September 2021

License

Commercial or Open Source

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

MIT License

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

JavaScript

Java, C++

Clojure

Server operating systems

All OS with a Java VM
Linux
OS X
Windows

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

Linux
OS X

for development

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

Data scheme

schema-free and OWL/RDFS-schema support; RDF shapes

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.

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

via views

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

only a subset of SQL 99

limited SQL, making use of Apache Calcite

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

JavaScript API

Java API
JDBC
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

View functions in JavaScript

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

none

Foreign keys

Referential integrity

yes

Constraint checking

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Transactions are executed single-threaded within stored procedures

ACID

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

Snapshots and command logging

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

User concepts

Access control

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains
11 September 2024

Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
30 August 2024

Using Entity Linking to Turn Your Graph into a Knowledge Graph
23 August 2024

Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
22 August 2024

The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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