DBMS > JaguarDB vs. Sadas Engine vs. SWC-DB vs. Tigris

System Properties Comparison JaguarDB vs. Sadas Engine vs. SWC-DB vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A high performance, scalable Wide Column DBMS

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Key-value store
Vector DBMS

Relational DBMS

Wide column store

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Time Series DBMS

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

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Score	0.05
Rank	#359	Overall
	#50	Document stores
	#52	Key-value stores
	#23	Search engines
	#37	Time Series DBMS

Website

www.jaguardb.com

www.sadasengine.com

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

www.tigrisdata.com

Technical documentation

www.jaguardb.com/support.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

www.tigrisdata.com/docs

Developer

DataJaguar, Inc.

SADAS s.r.l.

Alex Kashirin

Tigris Data, Inc.

Initial release

2015

2006

2020

2022

Current release

3.3 July 2023

8.0

0.5, April 2021

License

Commercial or Open Source

Open Source

GPL V3.0

commercial

free trial version available

Open Source

GPL V3

Open Source

Apache Version 2.0

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++

the server part. Clients available in other languages

C++

Server operating systems

Linux

AIX
Linux
Windows

Linux

Linux
macOS
Windows

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Proprietary protocol
Thrift

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

yes, using FoundationDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

User concepts

Access control

rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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