DBMS > Hypertable vs. Infobright vs. StarRocks vs. Yaacomo

System Properties Comparison Hypertable vs. Infobright vs. StarRocks vs. Yaacomo

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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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Wide column store

Relational DBMS

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

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

www.starrocks.io

yaacomo.com

Technical documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Hypertable Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

The Linux Foundation

since Feb 2023

Q2WEB GmbH

Initial release

2009

2005

2020

2009

Current release

0.9.8.11, March 2016

2.5.3, March 2023

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C++, Java

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
Windows

Linux

Android
Linux
Windows

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.

Secondary indexes

restricted

only exact value or prefix value scans

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

C++ API
Thrift

ADO.NET
JDBC
ODBC

JDBC
MySQL protocol

JDBC
ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range and hash)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Source-replica replication

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

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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