DBMS > Firebolt vs. GridDB vs. PostGIS vs. Sadas Engine

System Properties Comparison Firebolt vs. GridDB vs. PostGIS vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Scalable in-memory time series database optimized for IoT and Big Data

Spatial extension of PostgreSQL

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

Primary database model

Secondary database models

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.49
Rank	#148	Overall
	#68	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

Technical documentation

docs.firebolt.io

docs.griddb.net

postgis.net/documentation

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

Developer

Firebolt Analytics Inc.

Toshiba Corporation

SADAS s.r.l.

Initial release

2020

2013

2005

2006

Current release

5.1, August 2022

3.4.2, February 2024

8.0

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPL v2.0

commercial

free trial version available

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++

Server operating systems

hosted

Linux

AIX
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

APIs and other access methods

.Net
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

Supported programming languages

Go
JavaScript (Node.js)
Python

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

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

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

Source-replica replication

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

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'

User concepts

Access control

Access rights for users can be defined per database

yes

based on PostgreSQL

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

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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