DBMS > LeanXcale vs. Sequoiadb vs. SWC-DB vs. Tkrzw vs. Transbase

System Properties Comparison LeanXcale vs. Sequoiadb vs. SWC-DB vs. Tkrzw vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

NewSQL database with distributed OLTP and SQL

A high performance, scalable Wide Column DBMS

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Key-value store
Relational DBMS

Document store
Relational DBMS

Wide column store

Key-value store

Relational DBMS

Secondary database models

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	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.leanxcale.com

www.sequoiadb.com

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

dbmx.net/tkrzw

www.transaction.de/en/products/transbase.html

Technical documentation

www.sequoiadb.com/en/index.php?m=Files&a=index

www.transaction.de/en/products/transbase/features.html

Developer

LeanXcale

Sequoiadb Ltd.

Alex Kashirin

Mikio Hirabayashi

Transaction Software GmbH

Initial release

2015

2013

2020

1987

Current release

0.5, April 2021

0.9.3, August 2020

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

Open Source

GPL V3

Open Source

Apache Version 2.0

commercial

free development license

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

C++

C and C++

Server operating systems

Linux

Linux
macOS

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

yes

through Apache Derby

SQL-like query language

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

proprietary protocol using JSON

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
Java
Scala

.Net
C++
Java
PHP
Python

C++

C++
Java
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

yes

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

using specific database classes

User concepts

Access control

simple password-based access control

fine grained access rights according to SQL-standard

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