DBMS > Apache Impala vs. Infobright vs. InterSystems Caché vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Impala vs. Infobright vs. InterSystems Caché vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A multi-model DBMS and application server

Fully managed big data interactive analytics platform

Primary database model

Relational DBMS

Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

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	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Website

impala.apache.org

ignitetech.com/softwarelibrary/infobrightdb

www.intersystems.com/products/cache

azure.microsoft.com/services/data-explorer

Technical documentation

impala.apache.org/impala-docs.html

docs.intersystems.com

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Ignite Technologies Inc.; formerly InfoBright Inc.

InterSystems

Microsoft

Initial release

2013

2005

1997

2019

Current release

4.1.0, June 2022

2018.1.4, May 2020

cloud service with continuous releases

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

C++

Server operating systems

Linux

Linux
Windows

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

depending on used data model

Fixed schema with schema-less datatypes (dynamic)

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

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

Knowledge Grid Technology used instead

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
C++
Java

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

yes

query execution via MapReduce

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual 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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users, groups and roles

Azure Active Directory Authentication

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More resources

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