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DBMS > Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Rockset vs. Vertica

System Properties Comparison Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. Rockset vs. Vertica

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRockset  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionA widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platformA scalable, reliable search and analytics service in the cloud, built on RocksDBCloud 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 storeRelational DBMSRelational 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
Relational DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.82
Rank#212  Overall
#36  Document stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitehazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorerrockset.comwww.vertica.com
Technical documentationhazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.rockset.comvertica.com/­documentation
DeveloperHazelcastActian CorporationMicrosoftRocksetOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20081974 infooriginally developed at University Berkely in early 1970s201920192005
Current release5.3.6, November 202311.2, May 2022cloud service with continuous releases12.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++C++
Server operating systemsAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedhostedLinux
Data schemeschema-freeyesFixed 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 dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesdynamic typingyes
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 strategyno infobut tools for importing/exporting data from/to XML-files availableyesno infoingestion from XML files supportedno
Secondary indexesyesyesall fields are automatically indexedall fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetRead-only SQL queries, including JOINsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP RESTADO.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
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, Rnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceAutomatic shardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesMulti-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-sparknono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
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.yesnonono
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights for users and organizations can be defined via Rockset consolefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
HazelcastIngresMicrosoft Azure Data ExplorerRocksetVertica 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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HazelcastIngresMicrosoft Azure Data ExplorerRocksetVertica infoOpenText™ Vertica™
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