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

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

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Secondary database models

Document store

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	1.90
Rank	#134	Overall
	#62	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

arcadedb.com

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

www.firebolt.io

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.arcadedb.com

docs.dolthub.com

docs.firebolt.io

docs.microsoft.com/azure/synapse-analytics

Developer

Arcade Data

DoltHub Inc

Firebolt Analytics Inc.

Microsoft

Initial release

2021

2018

2020

2016

Current release

September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 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

Java

C++

Server operating systems

All OS with a Java VM

Linux
macOS
Windows

hosted

Data scheme

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

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

CLI Client
HTTP REST

.Net
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

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

C#
Java
PHP

Server-side scripts

Stored procedures

yes

currently in alpha release

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

Source-replica replication

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

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

relationship in graphs

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

User concepts

Access control

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

yes

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