DBMS > etcd vs. LevelDB vs. Memcached vs. Microsoft Azure Cosmos DB vs. TerminusDB

System Properties Comparison etcd vs. LevelDB vs. Memcached vs. Microsoft Azure Cosmos DB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Globally distributed, horizontally scalable, multi-model database service

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

etcd.io
github.com/etcd-io/etcd

github.com/google/leveldb

www.memcached.org

azure.microsoft.com/services/cosmos-db

terminusdb.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

github.com/google/leveldb/blob/main/doc/index.md

github.com/memcached/memcached/wiki

learn.microsoft.com/azure/cosmos-db

terminusdb.github.io/terminusdb/#

Developer

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

DataChemist Ltd.

Initial release

2011

2003

2014

2018

Current release

3.4, August 2019

1.23, February 2021

1.6.27, May 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

BSD license

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Prolog, Rust

Server operating systems

FreeBSD
Linux
Windows

experimental

Illumos
Linux
OS X
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON 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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like query language

SQL-like query language (WOQL)

APIs and other access methods

gRPC
JSON over HTTP

Proprietary protocol

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

JavaScript
Python

Server-side scripts

Stored procedures

JavaScript

yes

Triggers

yes, watching key changes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights can be defined down to the item level

Role-based access control

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