DBMS > Apache Druid vs. FeatureBase vs. Microsoft Azure Data Explorer vs. SpaceTime vs. SpatiaLite

System Properties Comparison Apache Druid vs. FeatureBase vs. Microsoft Azure Data Explorer vs. SpaceTime vs. SpatiaLite

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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Fully managed big data interactive analytics platform

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

Spatial extension of SQLite

Primary database model

Relational DBMS
Time Series DBMS

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	0.26
Rank	#304	Overall
	#138	Relational DBMS

Score	5.16
Rank	#69	Overall
	#37	Relational DBMS

Score	0.00
Rank	#396	Overall
	#8	Spatial DBMS

Score	1.72
Rank	#149	Overall
	#3	Spatial DBMS

Website

druid.apache.org

www.featurebase.com

azure.microsoft.com/services/data-explorer

www.mireo.com/spacetime

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

druid.apache.org/docs/latest/design

docs.featurebase.com

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

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Apache Software Foundation and contributors

Molecula and Pilosa Open Source Contributors

Microsoft

Mireo

Alessandro Furieri

Initial release

2012

2017

2019

2020

2008

Current release

29.0.1, April 2024

2022, May 2022

cloud service with continuous releases

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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++

Server operating systems

Linux
OS X
Unix

Linux
macOS

hosted

Linux

server-less

Data scheme

yes

schema-less columns are supported

yes

Fixed schema with schema-less datatypes (dynamic)

yes

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

SQL queries

Kusto Query Language (KQL), SQL subset

A subset of ANSI SQL is implemented

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

gRPC
JDBC
Kafka Connector
ODBC

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

RESTful HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
Python

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

C#
C++
Python

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

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

Sharding

Implicit feature of the cloud service

Fixed-grid hypercubes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

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

Real-time block device replication (DRBD)

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

Azure Active Directory Authentication

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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