DBMS > FoundationDB vs. Hypertable vs. SAP HANA vs. SAP SQL Anywhere vs. TDengine

System Properties Comparison FoundationDB vs. Hypertable vs. SAP HANA vs. SAP SQL Anywhere vs. TDengine

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

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

Description

Ordered key-value store. Core features are complimented by layers.

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

Time Series DBMS and big data platform

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Relational DBMS

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

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

github.com/apple/foundationdb

www.sap.com/products/hana.html

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

github.com/taosdata/TDengine
tdengine.com

Technical documentation

apple.github.io/foundationdb

help.sap.com/hana

help.sap.com/docs/SAP_SQL_Anywhere

docs.tdengine.com

Developer

FoundationDB

Hypertable Inc.

SAP

formerly Sybase

TDEngine, previously Taos Data

Initial release

2013

2009

2010

1992

2019

Current release

6.2.28, November 2020

0.9.8.11, March 2016

2.0 SPS07 (April 4, 2023), April 2023

17, July 2015

3.0, August 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

commercial

Open Source

AGPL V3, also commercial editions available

Cloud-based only

Only available as a cloud service

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

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

Linux
Windows

Data scheme

schema-free

some layers support schemas

schema-free

yes

Typing

predefined data types such as float or date

some layers support typing

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

supported in specific SQL layer only

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

C++ API
Thrift

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C++
Java
Perl
PHP
Python
Ruby

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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

in SQL-layer only

SQLScript, R

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

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

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

yes

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