DBMS > openGemini vs. Riak TS vs. Spark SQL vs. TerarkDB

System Properties Comparison openGemini vs. Riak TS vs. Spark SQL vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

Time Series DBMS

Relational DBMS

Key-value store

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

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.opengemini.org
github.com/openGemini

spark.apache.org/sql

github.com/bytedance/terarkdb

Technical documentation

docs.opengemini.org/guide

www.tiot.jp/riak-docs/riak/ts/latest

spark.apache.org/docs/latest/sql-programming-guide.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Huawei and openGemini community

Open Source, formerly Basho Technologies

Apache Software Foundation

ByteDance, originally Terark

Initial release

2022

2015

2014

2016

Current release

1.1, July 2023

3.0.0, September 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Erlang

Scala

C++

Server operating systems

Linux
Windows

Linux
OS X

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

Integer, Float, Boolean, String

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

restricted

SQL

Support of SQL

SQL-like query language

yes, limited

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

HTTP API
Native Erlang Interface

JDBC
ODBC

C++ API
Java API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Python
R
Scala

C++
Java

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

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

Administrators and common users accounts

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