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DBMS > Hazelcast vs. Microsoft Azure Table Storage vs. Pinecone vs. Prometheus

System Properties Comparison Hazelcast vs. Microsoft Azure Table Storage vs. Pinecone vs. Prometheus

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonPinecone  Xexclude from comparisonPrometheus  Xexclude from comparison
DescriptionA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsA managed, cloud-native vector databaseOpen-source Time Series DBMS and monitoring system
Primary database modelKey-value storeWide column storeVector DBMSTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitehazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.pinecone.ioprometheus.io
Technical documentationhazelcast.org/­imdg/­docsdocs.pinecone.io/­docs/­overviewprometheus.io/­docs
DeveloperHazelcastMicrosoftPinecone Systems, Inc
Initial release2008201220192015
Current release5.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemsAll OS with a Java VMhostedhostedLinux
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesString, Number, BooleanNumeric 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 strategynonono infoImport of XML data possible
Secondary indexesyesnono
SQL infoSupport of SQLSQL-like query languagenonono
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIRESTful HTTP APIRESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Python.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesnono
Triggersyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding
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.yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistencynone
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedoptimistic lockingno
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.yesnonono
User concepts infoAccess controlRole-based access controlAccess rights based on private key authentication or shared access signaturesno

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More resources
HazelcastMicrosoft Azure Table StoragePineconePrometheus
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