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DBMS > Greenplum vs. GridGain vs. Hive vs. Microsoft Azure Data Explorer

System Properties Comparison Greenplum vs. GridGain vs. Hive vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAnalytic 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.GridGain is an in-memory computing platform, built on Apache Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platform
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn oriented
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitegreenplum.orgwww.gridgain.comhive.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.greenplum.orgwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperPivotal Software Inc.GridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookMicrosoft
Initial release2005200720122019
Current release7.0.0, September 2023GridGain 8.5.13.1.3, April 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJava
Server operating systemsLinuxLinux
OS X
Solaris
Windows
All OS with a Java VMhosted
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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.yes infosince Version 4.2yesyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
Java
Perl
Python
R
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, R
Triggersyesyes (cache interceptors and events)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)selectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)yes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsAccess rights for users, groups and rolesAzure Active Directory Authentication

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More resources
GreenplumGridGainHiveMicrosoft Azure Data Explorer
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