DBMS > Heroic vs. Ingres vs. Percona Server for MongoDB vs. Yanza

System Properties Comparison Heroic vs. Ingres vs. Percona Server for MongoDB vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Well established RDBMS

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Time Series DBMS for IoT Applications

Primary database model

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

github.com/spotify/heroic

www.actian.com/databases/ingres

www.percona.com/mongodb/software/percona-server-for-mongodb

yanza.com

Technical documentation

spotify.github.io/heroic

docs.actian.com/ingres

docs.percona.com/percona-distribution-for-mongodb

Developer

Spotify

Actian Corporation

Percona

Yanza

Initial release

2014

1974

originally developed at University Berkely in early 1970s

2015

Current release

11.2, May 2022

3.4.10-2.10, November 2017

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL Version 2

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

C++

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Windows

Data scheme

schema-free

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

proprietary protocol using JSON

HTTP API

Supported programming languages

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Ingres Replicator

Source-replica replication

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
Immediate Consistency

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

MVCC

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

via In-Memory Engine

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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