DBMS > Alibaba Cloud TSDB vs. EventStoreDB vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison Alibaba Cloud TSDB vs. EventStoreDB vs. Microsoft Azure Data Explorer vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

A stable, reliable, and cost-effective online high-performance time series database service

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Fully managed big data interactive analytics platform

Spark SQL is a component on top of 'Spark Core' for structured data processing

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

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

Score	0.29
Rank	#301	Overall
	#26	Time Series DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/hitsdb

www.eventstore.com

azure.microsoft.com/services/data-explorer

spark.apache.org/sql

Technical documentation

www.alibabacloud.com/help/en/time-series-database/latest/what-is-tsdb

developers.eventstore.com

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Alibaba

Event Store Limited

Microsoft

Apache Software Foundation

Initial release

2012

2019

2014

Current release

21.2, February 2021

cloud service with continuous releases

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

Server operating systems

hosted

Linux
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

Numeric data and Strings

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

all fields are automatically indexed

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

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

JDBC
ODBC

Supported programming languages

Java

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes, utilizing Spark Core

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.

none

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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.

User concepts

Access control

Access managed on TSDB instance level

Azure Active Directory Authentication

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