DBMS > BigObject vs. Dolt vs. Faircom EDGE vs. H2

System Properties Comparison BigObject vs. Dolt vs. Faircom EDGE vs. H2

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store

Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.02
Rank	#368	Overall
	#54	Key-value stores
	#156	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

bigobject.io

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

www.faircom.com/products/faircom-edge

www.h2database.com

Technical documentation

docs.bigobject.io

docs.dolthub.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

www.h2database.com/html/main.html

Developer

BigObject, Inc.

DoltHub Inc

FairCom Corporation

Thomas Mueller

Initial release

2015

2018

1979

2005

Current release

V3, October 2020

2.2.220, July 2023

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2.0

commercial

Restricted, free version available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

ANSI C, C++

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
macOS
Windows

Android
Linux

ARM, x86
Raspbian
Windows

All OS with a Java VM

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL 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

SQL-like DML and DDL statements

yes

ANSI SQL queries

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

CLI Client
HTTP REST

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

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

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Java

Server-side scripts

Stored procedures

Lua

yes

currently in alpha release

yes

.Net, JavaScript, C/C++

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning

Customizable business rules for partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

Synchronous and asynchronous realtime replication based on transaction logs

With clustering: 2 database servers on different computers operate on identical copies of a database

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

when using SQL

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

across SQL and NoSQL

yes, multi-version concurrency control (MVCC)

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 user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

fine grained access rights according to SQL-standard

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