DBMS > Apache Druid vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. SAP IQ vs. SpaceTime

System Properties Comparison Apache Druid vs. Faircom EDGE vs. Microsoft Azure Data Explorer vs. SAP IQ vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Fully managed big data interactive analytics platform

Columnar RDBMS optimized for Big Data analytics

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

column oriented

Relational DBMS

column-oriented

Spatial DBMS

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

Relational DBMS

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	0.03
Rank	#380	Overall
	#59	Key-value stores
	#157	Relational DBMS

Score	5.16
Rank	#69	Overall
	#37	Relational DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Score	0.00
Rank	#396	Overall
	#8	Spatial DBMS

Website

druid.apache.org

www.faircom.com/products/faircom-edge

azure.microsoft.com/services/data-explorer

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.mireo.com/spacetime

Technical documentation

druid.apache.org/docs/latest/design

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

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

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation and contributors

FairCom Corporation

Microsoft

SAP, formerly Sybase

Mireo

Initial release

2012

1979

2019

1994

2020

Current release

29.0.1, April 2024

V3, October 2020

cloud service with continuous releases

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Restricted, free version available

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

ANSI C, C++

C++

Server operating systems

Linux
OS X
Unix

Android
Linux

ARM, x86
Raspbian
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-less columns are supported

Flexible Schema (defined schema, partial schema, schema free)

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

yes

ANSI SQL queries

Kusto Query Language (KQL), SQL subset

yes

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

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

ADO.NET
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

C#
C++
Python

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Yes, possible languages: KQL, Python, R

yes

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

File partitioning

Customizable business rules for partitioning

Sharding

Implicit feature of the cloud service

shared disk or shared nothing architectures with SAP IQ Multiplexer

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

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

SAP/Sybase Replication Server

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

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