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DBMS > Apache Druid vs. Greenplum vs. Manticore Search vs. Microsoft Azure Data Explorer vs. STSdb

System Properties Comparison Apache Druid vs. Greenplum vs. Manticore Search vs. Microsoft Azure Data Explorer vs. STSdb

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGreenplum  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Multi-storage database for search, including full-text search.Fully managed big data interactive analytics platformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSSearch engineRelational DBMS infocolumn orientedKey-value store
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infousing the Manticore Columnar LibraryDocument 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
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
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score0.23
Rank#317  Overall
#21  Search engines
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Websitedruid.apache.orggreenplum.orgmanticoresearch.comazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.greenplum.orgmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsPivotal Software Inc.Manticore SoftwareMicrosoftSTS Soft SC
Initial release20122005201720192011
Current release29.0.1, April 20247.0.0, September 20236.0, February 2023cloud service with continuous releases4.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0Open Source infoGPL version 2commercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#
Server operating systemsLinux
OS X
Unix
LinuxFreeBSD
Linux
macOS
Windows
hostedWindows
Data schemeyes infoschema-less columns are supportedyesFixed schemaFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infoprimitive types and user defined types (classes)
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.noyes infosince Version 4.2Can index from XMLyes
Secondary indexesyesyesyes infofull-text index on all search fieldsall fields are automatically indexedno
SQL infoSupport of SQLSQL for queryingyesSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
Java
Perl
Python
R
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
Server-side scripts infoStored proceduresnoyesuser defined functionsYes, possible languages: KQL, Python, Rno
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark 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 integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDyes infoisolated transactions for atomic changes and binary logging for safe writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
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-standardnoAzure Active Directory Authenticationno

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More resources
Apache DruidGreenplumManticore SearchMicrosoft Azure Data ExplorerSTSdb
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