DBMS > Couchbase vs. HyperSQL vs. KairosDB vs. Snowflake

System Properties Comparison Couchbase vs. HyperSQL vs. KairosDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Distributed Time Series DBMS based on Cassandra or H2

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

Primary database model

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

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.couchbase.com

hsqldb.org

github.com/kairosdb/kairosdb

www.snowflake.com

Technical documentation

docs.couchbase.com

hsqldb.org/web/hsqlDocsFrame.html

kairosdb.github.io

docs.snowflake.net/manuals/index.html

Developer

Couchbase, Inc.

Snowflake Computing Inc.

Initial release

2011

2001

2013

2014

Current release

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

2.7.2, June 2023

1.2.2, November 2018

License

Commercial or Open Source

Open Source

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

Open Source

based on BSD license

Open Source

Apache 2.0

commercial

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, C++, Go and Erlang

Java

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

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

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

SQL

Support of SQL

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

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

HTTP API

JDBC via HTTP
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

CLI Client
JDBC
ODBC

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC
Java

Java
JavaScript

Node.js
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

Java, SQL

user defined functions

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

none

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

none

selectable replication factor

based on Cassandra

yes

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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

Ephemeral buckets

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

simple password-based access control

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

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