DBMS > Bangdb vs. Heroic vs. SpaceTime vs. Titan vs. ToroDB

System Properties Comparison Bangdb vs. Heroic vs. SpaceTime vs. Titan vs. ToroDB

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Titan is a Graph DBMS optimized for distributed clusters.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

bangdb.com

github.com/spotify/heroic

www.mireo.com/spacetime

github.com/thinkaurelius/titan

github.com/torodb/server

Technical documentation

docs.bangdb.com

spotify.github.io/heroic

github.com/thinkaurelius/titan/wiki

Developer

Sachin Sinha, BangDB

Spotify

Mireo

Aurelius, owned by DataStax

8Kdata

Initial release

2012

2014

2020

2012

2016

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

commercial

Open Source

Apache license, version 2.0

Open Source

AGPL-V3

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, C++

Java

C++

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

string, integer, double, boolean, date, object_id

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

secondary, composite, nested, reverse, geospatial

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL like support with command line tool

A subset of ANSI SQL is implemented

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C
C#
C++
Java
Python

C#
C++
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Fixed-grid hypercubes

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Real-time block device replication (DRBD)

yes

Source-replica replication

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

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

yes

User authentification and security via Rexster Graph Server

Access rights for users and roles

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

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

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

Database Deep Dives: JanusGraph
8 August 2019, IBM

provided by Google News

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