DBMS > Heroic vs. HugeGraph vs. SiriDB

System Properties Comparison Heroic vs. HugeGraph vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

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

A fast-speed and highly-scalable Graph DBMS

Open Source Time Series DBMS

Primary database model

Time Series DBMS

Graph DBMS

Time Series DBMS

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

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	0.11
Rank	#346	Overall
	#32	Time Series DBMS

Website

github.com/spotify/heroic

github.com/hugegraph
hugegraph.apache.org

siridb.com

Technical documentation

spotify.github.io/heroic

hugegraph.apache.org/docs

docs.siridb.com

Developer

Spotify

Baidu

Cesbit

Initial release

2014

2018

2017

Current release

0.9

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
macOS
Unix

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

also supports composite index and range index

yes

SQL

Support of SQL

APIs and other access methods

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

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

Supported programming languages

Groovy
Java
Python

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

simple rights management via user accounts

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More resources

Recent citations in the news

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

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

SiriDB tijdreeks database analyseert time series data vanuit elke bron
22 January 2017, Dutch IT Channel

provided by Google News

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