DBMS > Firebolt vs. Sadas Engine vs. SwayDB vs. TimescaleDB vs. Valentina Server

System Properties Comparison Firebolt vs. Sadas Engine vs. SwayDB vs. TimescaleDB vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Object-relational database and reports server

Primary database model

Secondary database models

Relational DBMS

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

Score	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

Technical documentation

docs.firebolt.io

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

docs.timescale.com

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Firebolt Analytics Inc.

SADAS s.r.l.

Simer Plaha

Timescale

Paradigma Software

Initial release

2020

2006

2018

2017

1999

Current release

8.0

2.13.0, November 2023

5.7.5

License

Commercial or Open Source

commercial

free trial version available

Open Source

GNU Affero GPL V3.0

Open Source

Apache 2.0

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++

Scala

Server operating systems

hosted

AIX
Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

.Net
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ODBC

Supported programming languages

Go
JavaScript (Node.js)
Python

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

Java
Kotlin
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of operations

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

managed by 'Learn by Usage'

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

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