DBMS > Heroic vs. Hypertable vs. Riak TS vs. SpatiaLite

System Properties Comparison Heroic vs. Hypertable vs. Riak TS vs. SpatiaLite

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Spatial extension of SQLite

Primary database model

Secondary database models

Relational DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

github.com/spotify/heroic

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

spotify.github.io/heroic

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

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Spotify

Hypertable Inc.

Open Source, formerly Basho Technologies

Alessandro Furieri

Initial release

2014

2009

2015

2008

Current release

0.9.8.11, March 2016

3.0.0, September 2022

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Java

C++

Erlang

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X

server-less

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

yes

via Elasticsearch

restricted

only exact value or prefix value scans

restricted

yes

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

C++ API
Thrift

HTTP API
Native Erlang Interface

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

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

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More resources

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