DBMS > etcd vs. Kinetica vs. MySQL vs. RisingWave vs. SAP SQL Anywhere

System Properties Comparison etcd vs. Kinetica vs. MySQL vs. RisingWave vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.kinetica.com

www.mysql.com

www.risingwave.com/database

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.kinetica.com

dev.mysql.com/doc

docs.risingwave.com/docs/current/intro

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Kinetica

Oracle

since 2010, originally MySQL AB, then Sun

RisingWave Labs

SAP

formerly Sybase

Initial release

2012

1995

2022

1992

Current release

3.4, August 2019

7.1, August 2021

8.4.0, April 2024

1.2, September 2023

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

commercial

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.

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Implementation language

C, C++

C and C++

Rust

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

yes

APIs and other access methods

gRPC
JSON over HTTP

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
PostgreSQL wire protocol

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C++
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

UDFs in Python or Java

yes, in C/C++, Java, .Net or Perl

Triggers

yes, watching key changes

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

Users with fine-grained authorization concept

no user groups or roles

Users and Roles

fine grained access rights according to SQL-standard

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