DBMS > Dolt vs. Geode vs. KeyDB vs. SQLite

System Properties Comparison Dolt vs. Geode vs. KeyDB vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

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

Score	0.93
Rank	#194	Overall
	#90	Relational DBMS

Score	1.51
Rank	#147	Overall
	#25	Key-value stores

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

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

geode.apache.org

github.com/Snapchat/KeyDB
keydb.dev

www.sqlite.org

Technical documentation

docs.dolthub.com

geode.apache.org/docs

docs.keydb.dev

www.sqlite.org/docs.html

Developer

DoltHub Inc

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

EQ Alpha Technology Ltd.

Dwayne Richard Hipp

Initial release

2018

2002

2019

2000

Current release

1.1, February 2017

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

BSD-3

Open Source

Public Domain

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++

Server operating systems

Linux
macOS
Windows

All OS with a Java VM

the JDK (8 or later) is also required

Linux

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

not rigid because of 'dynamic typing' concept.

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

SQL-like query language (OQL)

yes

SQL-92 is not fully supported

APIs and other access methods

CLI Client
HTTP REST

Java Client API
Memcached protocol
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

.Net
All JVM based languages
C++
Groovy
Java
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

currently in alpha release

user defined functions

Lua

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

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.

Multi-source replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access rights per client and object definable

simple password-based access control and ACL

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