DBMS > Dolt vs. EJDB vs. FatDB vs. HyperSQL vs. InfluxDB

System Properties Comparison Dolt vs. EJDB vs. FatDB vs. HyperSQL vs. InfluxDB

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

DBMS for storing time series, events and metrics

Primary database model

Relational DBMS

Document store

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Spatial DBMS

with GEO package

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

Score	0.93
Rank	#194	Overall
	#90	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Website

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

github.com/Softmotions/ejdb

hsqldb.org

www.influxdata.com/products/influxdb-overview

Technical documentation

docs.dolthub.com

github.com/Softmotions/ejdb/blob/master/README.md

hsqldb.org/web/hsqlDocsFrame.html

docs.influxdata.com/influxdb

Developer

DoltHub Inc

Softmotions

FatCloud

Initial release

2018

2012

2001

2013

Current release

2.7.2, June 2023

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2

commercial

Open Source

based on BSD license

Open Source

MIT-License; commercial enterprise version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
macOS
Windows

server-less

Windows

All OS with a Java VM

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

Linux
OS X

through Homebrew

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

Numeric data and Strings

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

Via inetgration in SQL Server

yes

SQL-like query language

APIs and other access methods

CLI Client
HTTP REST

in-process shared library

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

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP API
JSON over UDP

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

All languages supporting JDBC/ODBC
Java

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

currently in alpha release

yes

via applications

Java, SQL

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

in enterprise version only

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.

none

selectable replication factor

none

selectable replication factor

in enterprise version only

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

typically not needed, however similar functionality with collection joins possible

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 Locking

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

Depending on used storage engine

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

fine grained access rights according to SQL-standard

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

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Recent citations in the news

Dolt- A Version Controlled Database
29 January 2024, iProgrammer

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

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

Radar trends to watch: September 2020
1 September 2020, O'Reilly Media

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HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

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Run and manage open source InfluxDB databases with Amazon Timestream
14 March 2024, AWS Blog

InfluxData avoids ’AI magic beans’ in InfluxDB time series database update for enterprises
4 September 2024, VentureBeat

InfluxData makes performance, storage improvements to InfluxDB 3.0
4 September 2024, InfoWorld

InfluxData's Latest Updates Optimize Time Series Data for Better Performance, Scale and Management
19 September 2024, Integration Developers

InfluxData Brings Higher Performance and New Features to InfluxDB 3.0 to Power Massive Time Series Workloads at Scale
4 September 2024, businesswire.com

provided by Google News

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