DBMS > CouchDB vs. Ignite vs. Memcached vs. Snowflake vs. Spark SQL

System Properties Comparison CouchDB vs. Ignite vs. Memcached vs. Snowflake vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

Cloud-based data warehousing service for structured and semi-structured data

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

Technical documentation

docs.couchdb.org/en/stable

apacheignite.readme.io/docs

github.com/memcached/memcached/wiki

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Apache Software Foundation

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

Apache Software Foundation

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2005

2015

2003

2014

Current release

3.3.3, December 2023

Apache Ignite 2.6

1.6.25, March 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache 2.0

Open Source

BSD license

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C++, Java, .Net

Scala

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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

Secondary indexes

yes

via views

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Proprietary protocol

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

none

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes (replicated cache)

none

Repcached, a Memcached patch, provides this functionallity

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

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

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 can be defined per database

Security Hooks for custom implementations

yes

using SASL (Simple Authentication and Security Layer) protocol

Users with fine-grained authorization concept, user roles and pluggable authentication

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