DBMS > EventStoreDB vs. InfinityDB vs. JanusGraph vs. Quasardb vs. STSdb

System Properties Comparison EventStoreDB vs. InfinityDB vs. JanusGraph vs. Quasardb vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A Java embedded Key-Value Store which extends the Java Map interface

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Distributed, high-performance timeseries database

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

developers.eventstore.com

boilerbay.com/infinitydb/manual

docs.janusgraph.org

doc.quasar.ai/master

Developer

Event Store Limited

Boiler Bay Inc.

Linux Foundation; originally developed as Titan by Aurelius

quasardb

STS Soft SC

Initial release

2012

2002

2017

2009

2011

Current release

21.2, February 2021

4.0

0.6.3, February 2023

3.14.1, January 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

GPLv2, 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

Java

C++

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

BSD
Linux
OS X
Windows

Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

integer and binary

yes

primitive types and user defined types (classes)

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

manual creation possible, using inversions based on multi-value capability

yes

with tags

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API

.NET Client API

Supported programming languages

Java

Clojure
Java
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

Relationships in graphs

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

User authentification and security via Rexster Graph Server

Cryptographically strong user authentication and audit trail

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