DBMS > CouchDB vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Kdb vs. SAP HANA

System Properties Comparison CouchDB vs. Google Cloud Bigtable vs. Hawkular Metrics vs. Kdb vs. SAP HANA

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

High performance Time Series DBMS

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store

Key-value store
Wide column store

Time Series DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

couchdb.apache.org

cloud.google.com/bigtable

www.hawkular.org

kx.com

www.sap.com/products/hana.html

Technical documentation

docs.couchdb.org/en/stable

cloud.google.com/bigtable/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

code.kx.com

help.sap.com/hana

Developer

Apache Software Foundation

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

Google

Community supported by Red Hat

Kx Systems, a division of First Derivatives plc

SAP

Initial release

2005

2015

2014

2000

kdb was released 2000, kdb+ in 2003

2010

Current release

3.3.3, December 2023

3.6, May 2018

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

commercial

free 32-bit version

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Erlang

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Appliance or cloud-service

Data scheme

schema-free

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

table attribute 'grouped'

yes

SQL

Support of SQL

SQL-like query language (q)

yes

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

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++
Go
Java
JavaScript (Node.js)
Python

Go
Java
Python
Ruby

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

SQLScript, R

Triggers

yes

via Hawkular Alerting

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

Sharding

based on Cassandra

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor

based on Cassandra

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

atomic operations within a single document possible

Atomic single-row operations

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

rights management via user accounts

yes

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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