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DBMS > Hazelcast vs. JSqlDb vs. Microsoft Azure Data Explorer vs. PouchDB vs. Vertica

System Properties Comparison Hazelcast vs. JSqlDb vs. Microsoft Azure Data Explorer vs. PouchDB vs. Vertica

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonJSqlDb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPouchDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionA widely adopted in-memory data gridJavaScript Query Language Database, stores JavaScript objects and primitivesFully managed big data interactive analytics platformJavaScript DBMS with an API inspired by CouchDBCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value storeDocument store
Object oriented DBMS
Relational DBMS infocolumn orientedDocument storeRelational DBMS infoColumn oriented
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
Spatial DBMS
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
Score2.28
Rank#115  Overall
#21  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitehazelcast.comjsqldb.org (offline)azure.microsoft.com/­services/­data-explorerpouchdb.comwww.vertica.com
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerpouchdb.com/­guidesvertica.com/­documentation
DeveloperHazelcastKonrad von BackstromMicrosoftApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20082018201920122005
Current release5.3.6, November 20230.8, December 2018cloud service with continuous releases7.1.1, June 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen SourcecommercialOpen Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaScriptC++
Server operating systemsAll OS with a Java VMLinux
macOS
Windows
hostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes
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 strategynoyesnono
Secondary indexesyesnoall fields are automatically indexedyes infovia viewsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languagenoKusto Query Language (KQL), SQL subsetnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
JavaScriptC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesfunctions in JavaScriptYes, possible languages: KQL, Python, RView functions in JavaScriptyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding infowith a proxy-based framework, named couchdb-loungehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing RocksDByesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlRole-based access controlAzure Active Directory Authenticationnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HazelcastJSqlDbMicrosoft Azure Data ExplorerPouchDBVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
HazelcastJSqlDbMicrosoft Azure Data ExplorerPouchDBVertica infoOpenText™ Vertica™
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