DBMS > Heroic vs. Riak TS vs. Teradata Aster vs. WakandaDB vs. Yanza

System Properties Comparison Heroic vs. Riak TS vs. Teradata Aster vs. WakandaDB vs. Yanza

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

Platform for big data analytics on multistructured data sources and types

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Time Series DBMS for IoT Applications

Primary database model

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

github.com/spotify/heroic

wakanda.github.io

yanza.com

Technical documentation

spotify.github.io/heroic

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

wakanda.github.io/doc

Developer

Spotify

Open Source, formerly Basho Technologies

Teradata

Wakanda SAS

Yanza

Initial release

2014

2015

2005

2012

2015

Current release

3.0.0, September 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Open Source

AGPLv3, extended commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

C++, JavaScript

Server operating systems

Linux
OS X

Linux

Linux
OS X
Windows

Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

schema-free

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.

yes

in Aster File Store

Secondary indexes

yes

via Elasticsearch

restricted

yes

SQL

Support of SQL

yes, limited

yes

APIs and other access methods

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

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

HTTP API

Supported programming languages

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
C#
C++
Java
Python
R

JavaScript

any language that supports HTTP calls

Server-side scripts

Stored procedures

Erlang

R packages

yes

Triggers

yes

pre-commit hooks and post-commit hooks

yes

Timer and event based

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

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

Teradata unveils improved QueryGrid connectors
21 April 2015, CIO

provided by Google News

Share this page