DBMS > Heroic vs. STSdb vs. TigerGraph vs. TinkerGraph vs. VoltDB

System Properties Comparison Heroic vs. STSdb vs. TigerGraph vs. TinkerGraph vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

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

Primary database model

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

Score	0.02
Rank	#368	Overall
	#38	Time Series DBMS

Score	0.03
Rank	#362	Overall
	#55	Key-value stores

Score	1.40
Rank	#152	Overall
	#14	Graph DBMS

Score	0.07
Rank	#346	Overall
	#35	Graph DBMS

Score	1.34
Rank	#155	Overall
	#71	Relational DBMS

Website

github.com/spotify/heroic

github.com/STSSoft/STSdb4

www.tigergraph.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

www.voltdb.com

Technical documentation

spotify.github.io/heroic

docs.tigergraph.com

docs.voltdb.com

Developer

Spotify

STS Soft SC

VoltDB Inc.

Initial release

2014

2011

2017

2009

2010

Current release

4.0.8, September 2015

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

commercial

Open Source

Apache 2.0

Open Source

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

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++

Java

Java, C++

Server operating systems

Windows

Linux

Linux
OS X

for development

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language (GSQL)

yes

only a subset of SQL 99

APIs and other access methods

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

.NET Client API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

TinkerPop 3

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C#
Java

C++
Java

Groovy
Java

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

optional

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

Users and roles with access to stored procedures

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

How Code Wizards load tested Heroic Labs’ Nakama to two million concurrent players with AWS
1 October 2024, AWS Blog

provided by Google News

TigerGraph unveils GenAI assistant, introduces new CEO
30 April 2024, TechTarget

Exploring the Power of Graph with Tigergraph
31 October 2024, AWS Blog

How TigerGraph CoPilot enables graph-augmented AI
30 April 2024, InfoWorld

TigerGraph raises $105M Series C for its enterprise graph database
17 February 2021, TechCrunch

An Introduction to Using TigerGraph with Go: Exploring COVID-19 Patient Cases
22 May 2022, Towards Data Science

provided by Google News

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune
3 June 2024, AWS Blog

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

provided by Google News

VoltDB Makes Key New Hires to Accelerate Telco Business Growth
28 October 2021, The Fast Mode

VoltDB Announces Latest Version Of Its In-Memory Database
9 February 2018, RTInsights

Solutions Review Sits Down with VoltDB CEO David Flower
17 April 2018, Solutions Review

MemSQL, VoltDB Vie For In-Memory Big Data Role
12 February 2015, InformationWeek

New startup from Postgres creator puts the database at heart of software stack
12 March 2024, TechCrunch

provided by Google News

Share this page