DBMS > Heroic vs. Microsoft Azure Synapse Analytics vs. OpenQM vs. Realm

System Properties Comparison Heroic vs. Microsoft Azure Synapse Analytics vs. OpenQM vs. Realm

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Editorial information provided by DB-Engines

Name

Description

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

QpenQM is a high-performance, self-tuning, multi-value DBMS

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

realm.io

Technical documentation

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

realm.io/docs

Developer

Spotify

Microsoft

Rocket Software, originally Martin Phillips

Realm, acquired by MongoDB in May 2019

Initial release

2014

2016

1993

2014

Current release

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Cloud-based only

Only available as a cloud service

yes

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

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

schema-free

yes

with some exceptions

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.

yes

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

ADO.NET
JDBC
ODBC

Supported programming languages

C#
Java
PHP

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

Transact SQL

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

In-Memory realm

User concepts

Access control

yes

Access rights can be defined down to the item level

yes

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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