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DBMS > Greenplum vs. Hazelcast vs. IRONdb vs. Microsoft Azure Data Explorer vs. Splunk

System Properties Comparison Greenplum vs. Hazelcast vs. IRONdb vs. Microsoft Azure Data Explorer vs. Splunk

Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonHazelcast  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSplunk  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.A widely adopted in-memory data gridA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformAnalytics Platform for Big Data
Primary database modelRelational DBMSKey-value storeTime Series DBMSRelational DBMS infocolumn orientedSearch engine
Secondary database modelsDocument store
Spatial 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
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score89.10
Rank#14  Overall
#2  Search engines
Websitegreenplum.orghazelcast.comwww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerwww.splunk.com
Technical documentationdocs.greenplum.orghazelcast.org/­imdg/­docsdocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerdocs.splunk.com/­Documentation/­Splunk
DeveloperPivotal Software Inc.HazelcastCirconus LLC.MicrosoftSplunk Inc.
Initial release20052008201720192003
Current release7.0.0, September 20235.3.6, November 2023V0.10.20, January 2018cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial infoLimited free edition and free developer edition available
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 languageJavaC and C++
Server operating systemsLinuxAll OS with a Java VMLinuxhostedLinux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyes 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.yes infosince Version 4.2yes infothe object must implement a serialization strategynoyesyes
Secondary indexesyesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetno infoSplunk Search Processing Language for search commands
APIs and other access methodsJDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Supported programming languagesC
Java
Perl
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
JavaScript
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes infoEvent Listeners, Executor Servicesyes, in LuaYes, possible languages: KQL, Python, Ryes
Triggersyesyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated Mapconfigurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednonono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching
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.noyesnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlnoAzure Active Directory AuthenticationAccess rights for users and roles

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More resources
GreenplumHazelcastIRONdbMicrosoft Azure Data ExplorerSplunk
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