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DBMS > FoundationDB vs. Hazelcast vs. Hypertable vs. Linter vs. Microsoft Azure Data Explorer

System Properties Comparison FoundationDB vs. Hazelcast vs. Hypertable vs. Linter vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonHazelcast  Xexclude from comparisonHypertable  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.A widely adopted in-memory data gridAn open source BigTable implementation based on distributed file systems such as HadoopRDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeWide column storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial 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
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitegithub.com/­apple/­foundationdbhazelcast.comlinter.ruazure.microsoft.com/­services/­data-explorer
Technical documentationapple.github.io/­foundationdbhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperFoundationDBHazelcastHypertable Inc.relex.ruMicrosoft
Initial release20132008200919902019
Current release6.2.28, November 20205.3.6, November 20230.9.8.11, March 2016cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoGNU version 3. Commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++C and C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinux
OS X
Windows infoan inofficial Windows port is available
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-free infosome layers support schemasschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateno infosome layers support typingyesnoyesyes 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.yes infothe object must implement a serialization strategynoyes
Secondary indexesnoyesrestricted infoonly exact value or prefix value scansyesall fields are automatically indexed
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query languagenoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
C++ API
Thrift
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresin SQL-layer onlyyes infoEvent Listeners, Executor Servicesnoyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersnoyes infoEventsnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapselectable replication factor on file system levelSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityin SQL-layer onlynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesno
User concepts infoAccess controlnoRole-based access controlnofine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
FoundationDBHazelcastHypertableLinterMicrosoft Azure Data Explorer
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