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DBMS > Hazelcast vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Oracle Berkeley DB vs. Prometheus

System Properties Comparison Hazelcast vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Oracle Berkeley DB vs. Prometheus

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionA widely adopted in-memory data gridFully managed big data interactive analytics platformExtremely fast embedded database for small devices, IoT and MobileWidely used in-process key-value storeOpen-source Time Series DBMS and monitoring system
Primary database modelKey-value storeRelational DBMS infocolumn orientedObject oriented DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMS
Secondary database modelsDocument 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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Websitehazelcast.comazure.microsoft.com/­services/­data-explorerobjectbox.iowww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlprometheus.io
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.iodocs.oracle.com/­cd/­E17076_05/­html/­index.htmlprometheus.io/­docs
DeveloperHazelcastMicrosoftObjectBox LimitedOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20082019201719942015
Current release5.3.6, November 2023cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache License 2.0Open Source infocommercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C, Java, C++ (depending on the Berkeley DB edition)Go
Server operating systemsAll OS with a Java VMhostedAndroid
iOS
Linux
macOS
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnoNumeric data only
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 infothe object must implement a serialization strategyyesnoyes infoonly with the Berkeley DB XML editionno infoImport of XML data possible
Secondary indexesyesall fields are automatically indexedyesyesno
SQL infoSupport of SQLSQL-like query languageKusto Query Language (KQL), SQL subsetnoyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native APIRESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rnonono
Triggersyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and serverSource-replica replicationyes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistencynone
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnonoyesno
User concepts infoAccess controlRole-based access controlAzure Active Directory Authenticationyesnono
More information provided by the system vendor
HazelcastMicrosoft Azure Data ExplorerObjectBoxOracle Berkeley DBPrometheus
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