DBMS > Dolt vs. FatDB vs. Heroic vs. ObjectBox vs. Sadas Engine

System Properties Comparison Dolt vs. FatDB vs. Heroic vs. ObjectBox vs. Sadas Engine

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Extremely fast embedded database for small devices, IoT and Mobile

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

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

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

github.com/spotify/heroic

objectbox.io

www.sadasengine.com

Technical documentation

docs.dolthub.com

spotify.github.io/heroic

docs.objectbox.io

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

Developer

DoltHub Inc

FatCloud

Spotify

ObjectBox Limited

SADAS s.r.l.

Initial release

2018

2012

2014

2017

2006

Current release

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

Apache License 2.0

commercial

free trial version available

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

Java

C and C++

C++

Server operating systems

Linux
macOS
Windows

Windows

Android
iOS
Linux
macOS
Windows

AIX
Linux
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

via Elasticsearch

yes

SQL

Support of SQL

yes

Via inetgration in SQL Server

yes

APIs and other access methods

CLI Client
HTTP REST

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Proprietary native API

JDBC
ODBC
Proprietary protocol

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

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

Server-side scripts

Stored procedures

yes

currently in alpha release

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

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.

selectable replication factor

yes

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate 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

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

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

Can implement custom security layer via applications

yes

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

More information provided by the system vendor

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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More resources

Recent citations in the news

Dolt- A Version Controlled Database
29 January 2024, iProgrammer

Top Data Version Control Tools for Machine Learning Research in 2023
24 July 2023, MarkTechPost

Dolt, a Relational Database with Git-Like Cloning Features
19 August 2020, The New Stack

Data Versioning at Scale: Chaos and Chaos Management
10 February 2023, InfoQ.com

Are you still not using Version Control for Data?
11 April 2020, Towards Data Science

provided by Google News

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