DBMS > ClickHouse vs. Hypertable vs. IBM Db2 vs. SAP HANA vs. Snowflake

System Properties Comparison ClickHouse vs. Hypertable vs. IBM Db2 vs. SAP HANA vs. Snowflake

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 high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

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

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Time Series DBMS

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	127.49
Rank	#8	Overall
	#5	Relational DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

clickhouse.com

www.ibm.com/products/db2

www.sap.com/products/hana.html

www.snowflake.com

Technical documentation

clickhouse.com/docs

www.ibm.com/docs/en/db2

help.sap.com/hana

docs.snowflake.net/manuals/index.html

Developer

Clickhouse Inc.

Hypertable Inc.

IBM

SAP

Snowflake Computing Inc.

Initial release

2016

2009

1983

host version

2010

2014

Current release

v24.3.2.23-lts, April 2024

0.9.8.11, March 2016

12.1, October 2016

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

commercial

free version is available

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++

C and C++

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Appliance or cloud-service

hosted

Data scheme

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

C++ API
Thrift

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

only with Windows/Unix/Linux Version

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

selectable replication factor on file system level

yes

with separate tools (MQ, InfoSphere)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

User concepts

Access control

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

yes

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

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