DBMS > Hypertable vs. Riak TS vs. SQream DB vs. Tkrzw

System Properties Comparison Hypertable vs. Riak TS vs. SQream DB vs. Tkrzw

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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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

a GPU-based, columnar RDBMS for big data analytics workloads

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

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

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

sqream.com

dbmx.net/tkrzw

Technical documentation

www.tiot.jp/riak-docs/riak/ts/latest

docs.sqream.com

Developer

Hypertable Inc.

Open Source, formerly Basho Technologies

SQream Technologies

Mikio Hirabayashi

Initial release

2009

2015

2017

2020

Current release

0.9.8.11, March 2016

3.0.0, September 2022

2022.1.6, December 2022

0.9.3, August 2020

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

commercial

Open Source

Apache Version 2.0

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++

Erlang

C++, CUDA, Haskell, Java, Scala

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X

Linux

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI Standard SQL Types

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

restricted

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

C++ API
Thrift

HTTP API
Native Erlang Interface

.Net
JDBC
ODBC

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++
Java
JavaScript (Node.js)
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Erlang

user defined functions in Python

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

using specific database classes

User concepts

Access control

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