DBMS > Apache Phoenix vs. ITTIA vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Phoenix vs. ITTIA vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Edge Time Series DBMS with Real-Time Stream Processing

Fully managed big data interactive analytics platform

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

column oriented

Secondary database models

Relational DBMS

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	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	0.36
Rank	#272	Overall
	#22	Time Series DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Website

phoenix.apache.org

www.ittia.com

azure.microsoft.com/services/data-explorer

Technical documentation

phoenix.apache.org

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

Developer

Apache Software Foundation

ITTIA L.L.C.

Microsoft

Initial release

2014

2007

2019

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

8.7

cloud service with continuous releases

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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 and C++

Server operating systems

Linux
Unix
Windows

Linux
Windows

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

Fixed schema

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

yes

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

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

all fields are automatically indexed

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API
WebSocket

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

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C
C++
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Database file passwords

Azure Active Directory Authentication

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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