DBMS > Couchbase vs. Hypertable vs. MySQL vs. Snowflake vs. TimesTen

System Properties Comparison Couchbase vs. Hypertable vs. MySQL vs. Snowflake vs. TimesTen

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

An open source BigTable implementation based on distributed file systems such as Hadoop

Widely used open source RDBMS

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

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
Spatial DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.couchbase.com

www.mysql.com

www.snowflake.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.couchbase.com

dev.mysql.com/doc

docs.snowflake.net/manuals/index.html

docs.oracle.com/database/timesten-18.1

Developer

Couchbase, Inc.

Hypertable Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Snowflake Computing Inc.

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2011

2009

1995

2014

1998

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

0.9.8.11, March 2016

8.4.0, April 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

GNU version 3. Commercial license available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++, Go and Erlang

C++

C and C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

FreeBSD
Linux
OS X
Solaris
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

with proprietary extensions

yes

APIs and other access methods

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

C++ API
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C++
Java
Perl
PHP
Python
Ruby

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

JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

proprietary syntax

user defined functions

PL/SQL

Triggers

yes

via the TAP protocol

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic Sharding

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor on file system level

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Users with fine-grained authorization concept

no user groups or roles

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

fine grained access rights according to SQL-standard

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