DBMS > Heroic vs. IBM Db2 warehouse vs. Machbase Neo vs. SAP SQL Anywhere vs. Yanza

System Properties Comparison Heroic vs. IBM Db2 warehouse vs. Machbase Neo vs. SAP SQL Anywhere vs. Yanza

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

Cloud-based data warehousing service

TimeSeries DBMS for AIoT and BigData

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

github.com/spotify/heroic

www.ibm.com/products/db2/warehouse

machbase.com

www.sap.com/products/technology-platform/sql-anywhere.html

yanza.com

Technical documentation

spotify.github.io/heroic

machbase.com/dbms

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Spotify

IBM

Machbase

SAP

formerly Sybase

Yanza

Initial release

2014

2013

1992

2015

Current release

V8.0, August 2023

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free test version available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

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

hosted

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

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.

Import/export of XML data possible

yes

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

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

.NET Client API
JDBC
ODBC
OLE DB

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
HTTP API
JDBC
ODBC

HTTP API

Supported programming languages

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

any language that supports HTTP calls

Server-side scripts

Stored procedures

PL/SQL, SQL PL

yes, in C/C++, Java, .Net or Perl

Triggers

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

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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