DBMS > Hypertable vs. IBM Db2 vs. RavenDB vs. SQLite

System Properties Comparison Hypertable vs. IBM Db2 vs. RavenDB vs. SQLite

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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

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Widely used embeddable, in-process RDBMS

Primary database model

Wide column store

Relational DBMS

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

Document store

Relational DBMS

Secondary database models

Document store
RDF store

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

with Db2 Spatial Extender

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.ibm.com/products/db2

ravendb.net

www.sqlite.org

Technical documentation

www.ibm.com/docs/en/db2

ravendb.net/docs

www.sqlite.org/docs.html

Developer

Hypertable Inc.

IBM

Hibernating Rhinos

Dwayne Richard Hipp

Initial release

2009

1983

host version

2010

2000

Current release

0.9.8.11, March 2016

12.1, October 2016

5.4, July 2022

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

free version is available

Open Source

AGPL version 3, commercial license available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
macOS
Raspberry Pi
Windows

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like query language (RQL)

yes

SQL-92 is not fully supported

APIs and other access methods

C++ API
Thrift

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

yes

with separate tools (MQ, InfoSphere)

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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