DBMS > BoltDB vs. Heroic vs. mSQL vs. Teradata Aster vs. Yanza

System Properties Comparison BoltDB vs. Heroic vs. mSQL vs. Teradata Aster 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

An embedded key-value store for Go.

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Platform for big data analytics on multistructured data sources and types

Time Series DBMS for IoT Applications

Primary database model

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

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Website

github.com/boltdb/bolt

github.com/spotify/heroic

hughestech.com.au/products/msql

yanza.com

Technical documentation

spotify.github.io/heroic

Developer

Spotify

Hughes Technologies

Teradata

Yanza

Initial release

2013

2014

1994

2005

2015

Current release

4.4, October 2021

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

commercial

free licenses can be provided

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

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux

Windows

Data scheme

schema-free

yes

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

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

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

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

APIs and other access methods

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

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

HTTP API

Supported programming languages

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C#
C++
Java
Python
R

any language that supports HTTP calls

Server-side scripts

Stored procedures

R packages

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

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

none

Eventual Consistency
Immediate Consistency

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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

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