DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Druid vs. BaseX vs. GeoSpock vs. Microsoft Azure Data Explorer vs. SpatiaLite

System Properties Comparison Apache Druid vs. BaseX vs. GeoSpock vs. Microsoft Azure Data Explorer vs. SpatiaLite

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBaseX  Xexclude from comparisonGeoSpock  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpatiaLite  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Spatial and temporal data processing engine for extreme data scaleFully managed big data interactive analytics platformSpatial extension of SQLite
Primary database modelRelational DBMS
Time Series DBMS
Native XML DBMSRelational DBMSRelational DBMS infocolumn orientedSpatial DBMS
Secondary database modelsTime Series DBMSDocument store infoIf 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 infothis 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 infosupport 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 infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score1.90
Rank#136  Overall
#4  Native XML DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score1.72
Rank#149  Overall
#3  Spatial DBMS
Websitedruid.apache.orgbasex.orggeospock.comazure.microsoft.com/­services/­data-explorerwww.gaia-gis.it/­fossil/­libspatialite/­index
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.basex.orgdocs.microsoft.com/­en-us/­azure/­data-explorerwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperApache Software Foundation and contributorsBaseX GmbHGeoSpockMicrosoftAlessandro Furieri
Initial release2012200720192008
Current release29.0.1, April 202410.7, August 20232.0, September 2019cloud service with continuous releases5.0.0, August 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoBSD licensecommercialcommercialOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava, JavascriptC++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
hostedhostedserver-less
Data schemeyes infoschema-less columns are supportedschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoyesno
Secondary indexesyesyestemporal, categoricalall fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingnoANSI SQL for query only (using Presto)Kusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
JDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyesnoYes, possible languages: KQL, Python, Rno
Triggersnoyes infovia eventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneAutomatic shardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanomultiple readers, single writernonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemUsers with fine-grained authorization concept on 4 levelsAccess rights for users can be defined per tableAzure Active Directory Authenticationno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache DruidBaseXGeoSpockMicrosoft Azure Data ExplorerSpatiaLite
DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Imply Data gives Apache Druid schema auto-discover capability
6 June 2023, SiliconANGLE News

Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ...
6 June 2023, Business Wire

provided by Google News

XML Injection Attacks: What to Know About XPath, XQuery, XXE & More
18 May 2022, Hashed Out by The SSL Store™

9 Skills You Need to Become a Data Engineer
2 November 2022, KDnuggets

provided by Google News

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

GeoSpock receives $5.4m as strategic investment
5 October 2020, Geospatial World

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

General availability: New KQL function to enrich your data analysis with geographic context | Azure updates
6 June 2023, Microsoft

What is Microsoft Fabric? A big tech stack for big data
9 February 2024, InfoWorld

Public Preview: Azure Cosmos DB to Azure Data Explorer Synapse Link | Azure updates
9 January 2023, Microsoft

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here