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DBMS > Hazelcast vs. Hive vs. Ingres vs. Microsoft Azure Data Explorer vs. XTDB

System Properties Comparison Hazelcast vs. Hive vs. Ingres vs. Microsoft Azure Data Explorer vs. XTDB

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHive  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionA widely adopted in-memory data griddata warehouse software for querying and managing large distributed datasets, built on HadoopWell established RDBMSFully managed big data interactive analytics platformA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS infocolumn orientedDocument store
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.18
Rank#332  Overall
#46  Document stores
Websitehazelcast.comhive.apache.orgwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorergithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationhazelcast.org/­imdg/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorerwww.xtdb.com/­docs
DeveloperHazelcastApache Software Foundation infoinitially developed by FacebookActian CorporationMicrosoftJuxt Ltd.
Initial release200820121974 infooriginally developed at University Berkely in early 1970s20192019
Current release5.3.6, November 20233.1.3, April 202211.2, May 2022cloud service with continuous releases1.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2commercialcommercialOpen Source infoMIT License
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 languageJavaJavaCClojure
Server operating systemsAll OS with a Java VMAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes, extensible-data-notation format
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
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsyesKusto Query Language (KQL), SQL subsetlimited SQL, making use of Apache Calcite
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
JDBC
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Clojure
Java
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infouser defined functions and integration of map-reduceyesYes, possible languages: KQL, Python, Rno
Triggersyes infoEventsnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapselectable replication factorIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
HazelcastHiveIngresMicrosoft Azure Data ExplorerXTDB infoformerly named Crux
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