DBMS > Hypertable vs. SAP HANA vs. SAP SQL Anywhere vs. Snowflake

System Properties Comparison Hypertable vs. SAP HANA vs. SAP SQL Anywhere vs. Snowflake

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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

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

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.sap.com/products/hana.html

www.sap.com/products/technology-platform/sql-anywhere.html

www.snowflake.com

Technical documentation

help.sap.com/hana

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

Developer

Hypertable Inc.

SAP

formerly Sybase

Snowflake Computing Inc.

Initial release

2009

2010

1992

2014

Current release

0.9.8.11, March 2016

2.0 SPS07 (April 4, 2023), April 2023

17, July 2015

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license 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.

Implementation language

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

C++ API
Thrift

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

SQLScript, R

yes, in C/C++, Java, .Net or Perl

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes

Source-replica replication

Database mirroring

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

yes

fine grained access rights according to SQL-standard

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

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