DBMS > Heroic vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. Oracle Coherence

System Properties Comparison Heroic vs. Microsoft Azure Data Explorer vs. Microsoft SQL Server vs. Oracle Coherence

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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

Fully managed big data interactive analytics platform

Microsofts flagship relational DBMS

Oracles in-memory data grid solution

Primary database model

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Graph DBMS
Spatial DBMS

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

github.com/spotify/heroic

azure.microsoft.com/services/data-explorer

www.microsoft.com/en-us/sql-server

www.oracle.com/java/coherence

Technical documentation

spotify.github.io/heroic

docs.microsoft.com/en-us/azure/data-explorer

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/middleware/standalone/coherence

Developer

Spotify

Microsoft

Oracle

Initial release

2014

2019

1989

2007

Current release

cloud service with continuous releases

SQL Server 2022, November 2022

14.1, August 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux
Windows

All OS with a Java VM

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

schema-free

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

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

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C++
Java

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

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