DBMS > Dolt vs. Firebolt vs. HyperSQL vs. Microsoft Azure Synapse Analytics

System Properties Comparison Dolt vs. Firebolt vs. HyperSQL vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Relational DBMS

Secondary database models

Document store

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

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

github.com/dolthub/dolt
www.dolthub.com

www.firebolt.io

hsqldb.org

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.dolthub.com

docs.firebolt.io

hsqldb.org/web/hsqlDocsFrame.html

docs.microsoft.com/azure/synapse-analytics

Developer

DoltHub Inc

Firebolt Analytics Inc.

Microsoft

Initial release

2018

2020

2001

2016

Current release

2.7.2, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

based on BSD license

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

Java

C++

Server operating systems

Linux
macOS
Windows

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Data scheme

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

yes

APIs and other access methods

CLI Client
HTTP REST

.Net
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET
JDBC
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC
Java

C#
Java
PHP

Server-side scripts

Stored procedures

yes

currently in alpha release

Java, SQL

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

depending on storage layer

none

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

Only one user is configurable, and must be specified in the config file at startup

fine grained access rights according to SQL-standard

yes

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