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DBMS > Apache Druid vs. Fujitsu Enterprise Postgres vs. HBase vs. Microsoft Azure Data Explorer vs. SpaceTime

System Properties Comparison Apache Druid vs. Fujitsu Enterprise Postgres vs. HBase vs. Microsoft Azure Data Explorer vs. SpaceTime

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSpaceTime  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Wide-column store based on Apache Hadoop and on concepts of BigTableFully managed big data interactive analytics platformSpaceTime is a spatio-temporal DBMS with a focus on performance.
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSWide column storeRelational DBMS infocolumn orientedSpatial DBMS
Secondary database modelsDocument store
Spatial DBMS
Document 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
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Websitedruid.apache.orgwww.postgresql.fastware.comhbase.apache.orgazure.microsoft.com/­services/­data-explorerwww.mireo.com/­spacetime
Technical documentationdruid.apache.org/­docs/­latest/­designwww.postgresql.fastware.com/­product-manualshbase.apache.org/­book.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftMireo
Initial release2012200820192020
Current release29.0.1, April 2024Fujitsu Enterprise Postgres 14, January 20222.3.4, January 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJavaC++
Server operating systemsLinux
OS X
Unix
Linux
Windows
Linux
Unix
Windows infousing Cygwin
hostedLinux
Data schemeyes infoschema-less columns are supportedyesschema-free, schema definition possibleFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes 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 indexesyesyesnoall fields are automatically indexedno
SQL infoSupport of SQLSQL for queryingyesnoKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
C++
Python
Server-side scripts infoStored proceduresnouser defined functionsyes infoCoprocessors in JavaYes, possible languages: KQL, Python, Rno
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedpartitioning by range, list and by hashShardingSharding infoImplicit feature of the cloud serviceFixed-grid hypercubes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Real-time block device replication (DRBD)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAzure Active Directory Authenticationyes

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More resources
Apache DruidFujitsu Enterprise PostgresHBaseMicrosoft Azure Data ExplorerSpaceTime
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