DBMS > H2GIS vs. HEAVY.AI vs. OpenQM vs. Tarantool

System Properties Comparison H2GIS vs. HEAVY.AI vs. OpenQM vs. Tarantool

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Spatial DBMS

Relational DBMS

Multivalue DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

www.h2gis.org

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.tarantool.io

Technical documentation

www.h2gis.org/docs/home

docs.heavy.ai

www.tarantool.io/en/doc

Developer

CNRS

HEAVY.AI, Inc.

Rocket Software, originally Martin Phillips

Initial release

2013

2016

1993

2008

Current release

5.10, January 2022

3.4-12

2.10.0, May 2022

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

Apache Version 2; enterprise edition available

Open Source

GPLv2, extended commercial license available

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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++ and CUDA

C and C++

Server operating systems

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

BSD
Linux
macOS

Data scheme

yes

with some exceptions

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC
Thrift
Vega

Open binary protocol

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

.Net
Basic
C
Java
Objective C
PHP
Python

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

yes

based on H2

yes

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

yes

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Multi-source replication

yes

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

yes

based on H2

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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