DBMS > LeanXcale vs. Riak TS vs. SWC-DB vs. Teradata

System Properties Comparison LeanXcale vs. Riak TS vs. SWC-DB vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

A high performance, scalable Wide Column DBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

www.leanxcale.com

github.com/kashirin-alex/swc-db
www.swcdb.org

www.teradata.com

Technical documentation

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

docs.teradata.com

Developer

LeanXcale

Open Source, formerly Basho Technologies

Alex Kashirin

Teradata

Initial release

2015

2020

1984

Current release

3.0.0, September 2022

0.5, April 2021

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

GPL V3

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.

Implementation language

Erlang

C++

Server operating systems

Linux
OS X

Linux

hosted
Linux

Data scheme

yes

schema-free

yes

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

restricted

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

through Apache Derby

yes, limited

SQL-like query language

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP API
Native Erlang Interface

Proprietary protocol
Thrift

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C
Java
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++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

Erlang

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

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

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

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More resources

DB-Engines blog posts

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