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DBMS > Databend vs. Hazelcast vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer

System Properties Comparison Databend vs. Hazelcast vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityA widely adopted in-memory data gridSearch-as-a-service for web and mobile app developmentFully managed big data interactive analytics platform
Primary database modelRelational DBMSKey-value storeSearch engineRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Vector DBMSDocument 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
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score5.52
Rank#59  Overall
#6  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
hazelcast.comazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.databend.comhazelcast.org/­imdg/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDatabend LabsHazelcastMicrosoftMicrosoft
Initial release2021200820152019
Current release1.0.59, April 20235.3.6, November 2023V1cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJava
Server operating systemshosted
Linux
macOS
All OS with a Java VMhostedhosted
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
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-types
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.noyes infothe object must implement a serialization strategynoyes
Secondary indexesnoyesyesall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like query languagenoKusto Query Language (KQL), SQL subset
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesnoYes, possible languages: KQL, Python, R
Triggersnoyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoReplicated Mapyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesone or two-phase-commit; repeatable reads; read commitednono
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.yesnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesRole-based access controlyes infousing Azure authenticationAzure Active Directory Authentication

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DatabendHazelcastMicrosoft Azure AI SearchMicrosoft Azure Data Explorer
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