DBMS > etcd vs. eXtremeDB vs. Riak TS vs. SAP SQL Anywhere vs. Snowflake

System Properties Comparison etcd vs. eXtremeDB vs. Riak TS vs. SAP SQL Anywhere vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Key-value store

Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.mcobject.com

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

www.snowflake.com

Technical documentation

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

www.mcobject.com/docs/extremedb.htm

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

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

Developer

McObject

Open Source, formerly Basho Technologies

SAP

formerly Sybase

Snowflake Computing Inc.

Initial release

2001

2015

1992

2014

Current release

3.4, August 2019

8.2, 2021

3.0.0, September 2022

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Erlang

Server operating systems

FreeBSD
Linux
Windows

experimental

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

support of XML interfaces available

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes, limited

yes

APIs and other access methods

gRPC
JSON over HTTP

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

HTTP API
Native Erlang Interface

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

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

.Net
C
C#
C++
Java
Lua
Python
Scala

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Erlang

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

user defined functions

Triggers

yes, watching key changes

yes

by defining events

yes

pre-commit hooks and post-commit hooks

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

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

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

selectable replication factor

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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