DBMS > Heroic vs. Microsoft Azure Synapse Analytics vs. SAP HANA vs. SiteWhere

System Properties Comparison Heroic vs. Microsoft Azure Synapse Analytics vs. SAP HANA vs. SiteWhere

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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

In-memory, column based data store. Available as appliance or cloud service

M2M integration platform for persisting/querying time series data

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/hana.html

github.com/sitewhere/sitewhere

Technical documentation

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

help.sap.com/hana

sitewhere1.sitewhere.io/index.html

Developer

Spotify

Microsoft

SAP

SiteWhere

Initial release

2014

2016

2010

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Java

Server operating systems

hosted

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined scheme

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.

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

JDBC
ODBC

HTTP REST

Supported programming languages

C#
Java
PHP

Server-side scripts

Stored procedures

Transact SQL

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

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

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

User concepts

Access control

yes

Users with fine-grained authorization concept

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