DBMS > Galaxybase vs. JanusGraph vs. SiriDB vs. TimescaleDB vs. Tkrzw

System Properties Comparison Galaxybase vs. JanusGraph vs. SiriDB vs. TimescaleDB vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

A Graph DBMS optimized for distributed clusters

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

Open Source Time Series DBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Graph DBMS

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

Technical documentation

docs.janusgraph.org

docs.siridb.com

docs.timescale.com

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Linux Foundation; originally developed as Titan by Aurelius

Cesbit

Timescale

Mikio Hirabayashi

Initial release

2017

2020

Current release

Nov 20, November 2021

0.6.3, February 2023

2.15.0, May 2024

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

C and Java

Java

C++

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux

Linux
OS X
Windows

Linux
macOS

Data scheme

Strong typed schema

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Secondary indexes

yes

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Go
Java
Python

Clojure
Java
Python

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined procedures and functions

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

Sharding

yes, across time and space (hash partitioning) attributes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication with hot standby and reads on replicas

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

yes

Transaction concepts

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

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

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

Role-based access control

User authentification and security via Rexster Graph Server

simple rights management via user accounts

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Database Deep Dives: JanusGraph
8 August 2019, IBM

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

Compose for JanusGraph arrives on Bluemix
15 September 2017, IBM

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, azure.microsoft.com

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News

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