DBMS > Heroic vs. OpenQM vs. SpatiaLite vs. TerarkDB

System Properties Comparison Heroic vs. OpenQM vs. SpatiaLite vs. TerarkDB

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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

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

Spatial extension of SQLite

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	1.56
Rank	#142	Overall
	#3	Spatial DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

github.com/spotify/heroic

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

www.gaia-gis.it/fossil/libspatialite/index

github.com/bytedance/terarkdb

Technical documentation

spotify.github.io/heroic

www.gaia-gis.it/gaia-sins/spatialite_topics.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Spotify

Rocket Software, originally Martin Phillips

Alessandro Furieri

ByteDance, originally Terark

Initial release

2014

1993

2008

2016

Current release

3.4-12

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

server-less

Data scheme

schema-free

yes

with some exceptions

yes

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

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

C++ API
Java API

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Access rights can be defined down to the item level

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