DBMS > gStore vs. HEAVY.AI vs. SiriDB vs. XTDB

System Properties Comparison gStore vs. HEAVY.AI vs. SiriDB vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

A native Graph DBMS to store and maintain very large RDF datasets.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Open Source Time Series DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

en.gstore.cn

github.com/heavyai/heavydb
www.heavy.ai

siridb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

en.gstore.cn/#/enDocs

docs.heavy.ai

docs.siridb.com

www.xtdb.com/docs

Developer

HEAVY.AI, Inc.

Cesbit

Juxt Ltd.

Initial release

2016

2017

2019

Current release

1.2, November 2023

5.10, January 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache Version 2; enterprise edition available

Open Source

MIT License

Open Source

MIT License

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++ and CUDA

Clojure

Server operating systems

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data

yes, extensible-data-notation format

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

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API
SPARQL 1.1

JDBC
ODBC
Thrift
Vega

HTTP API

HTTP REST
JDBC

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

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

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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, Role-Based Access Control (RBAC) supported

fine grained access rights according to SQL-standard

simple rights management via user accounts

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