DBMS > Badger vs. KeyDB vs. Memcached vs. Microsoft Azure Synapse Analytics vs. MySQL

System Properties Comparison Badger vs. KeyDB vs. Memcached vs. Microsoft Azure Synapse Analytics vs. MySQL

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

In-memory key-value store, originally intended for caching

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

Widely used open source RDBMS

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

github.com/dgraph-io/badger

github.com/Snapchat/KeyDB
keydb.dev

www.memcached.org

azure.microsoft.com/services/synapse-analytics

www.mysql.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.keydb.dev

github.com/memcached/memcached/wiki

docs.microsoft.com/azure/synapse-analytics

dev.mysql.com/doc

Developer

DGraph Labs

EQ Alpha Technology Ltd.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2017

2019

2003

2016

1995

Current release

1.6.25, March 2024

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD-3

Open Source

BSD license

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

FreeBSD
Linux
OS X
Unix
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

partial

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

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

by using the Redis Search module

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

Proprietary protocol

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C#
Java
PHP

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

Transact SQL

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding, horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

not for MyISAM storage engine

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

simple password-based access control and ACL

yes

using SASL (Simple Authentication and Security Layer) protocol

yes

Users with fine-grained authorization concept

no user groups or roles

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