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DBMS > Apache Drill vs. Citus vs. GridDB vs. Hazelcast vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Drill vs. Citus vs. GridDB vs. Hazelcast vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Drill  Xexclude from comparisonCitus  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionSchema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLScalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSKey-value storeRelational DBMS infocolumn oriented
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Document 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
Score2.02
Rank#124  Overall
#22  Document stores
#59  Relational DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitedrill.apache.orgwww.citusdata.comgriddb.nethazelcast.comazure.microsoft.com/­services/­data-explorer
Technical documentationdrill.apache.org/­docsdocs.citusdata.comdocs.griddb.nethazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationToshiba CorporationHazelcastMicrosoft
Initial release20122010201320082019
Current release1.20.3, January 20238.1, December 20185.1, August 20225.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL, commercial license also availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++Java
Server operating systemsLinux
OS X
Windows
LinuxLinuxAll OS with a Java VMhosted
Data schemeschema-freeyesyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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 infospecific XML type available, but no XML query functionalitynoyes infothe object must implement a serialization strategyyes
Secondary indexesnoyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL SELECT statement is SQL:2003 compliantyes infostandard, with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC++.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, R
Triggersnoyesyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentDepending on the underlying data sourceyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.Depending on the underlying data sourcenoyesyesno
User concepts infoAccess controlDepending on the underlying data sourcefine grained access rights according to SQL-standardAccess rights for users can be defined per databaseRole-based access controlAzure Active Directory Authentication
More information provided by the system vendor
Apache DrillCitusGridDBHazelcastMicrosoft Azure Data Explorer
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache DrillCitusGridDBHazelcastMicrosoft Azure Data Explorer
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