DBMS > Apache Impala vs. CouchDB vs. Memcached vs. Postgres-XL vs. RocksDB

System Properties Comparison Apache Impala vs. CouchDB vs. Memcached vs. Postgres-XL vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

Document store
Spatial DBMS

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Trend Chart

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

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

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.couchdb.org/en/stable

github.com/memcached/memcached/wiki

www.postgres-xl.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Facebook, Inc.

Initial release

2013

2005

2003

2014

since 2012, originally named StormDB

2013

Current release

4.1.0, June 2022

3.3.3, December 2023

1.6.25, March 2024

10 R1, October 2018

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

Open Source

BSD license

Open Source

Mozilla public license

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Erlang

C++

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Unix
Windows

Linux
macOS

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

XML type, but no XML query functionality

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

Proprietary protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

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

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions in JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

MVCC

yes

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic 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

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users can be defined per database

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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