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DBMS > Ehcache vs. FeatureBase vs. Microsoft Azure Data Explorer

System Properties Comparison Ehcache vs. FeatureBase vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFeatureBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Fully managed big data interactive analytics platform
Primary database modelKey-value storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument 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
Score5.23
Rank#68  Overall
#8  Key-value stores
Score0.26
Rank#304  Overall
#138  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.ehcache.orgwww.featurebase.comazure.microsoft.com/­services/­data-explorer
Technical documentationwww.ehcache.org/­documentationdocs.featurebase.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperTerracotta Inc, owned by Software AGMolecula and Pilosa Open Source ContributorsMicrosoft
Initial release200920172019
Current release3.10.0, March 20222022, May 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGo
Server operating systemsAll OS with a Java VMLinux
macOS
hosted
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)
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-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.nonoyes
Secondary indexesnonoall fields are automatically indexed
SQL infoSupport of SQLnoSQL queriesKusto Query Language (KQL), SQL subset
APIs and other access methodsJCachegRPC
JDBC
Kafka Connector
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaJava
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, R
Triggersyes infoCache Event Listenersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlnoAzure Active Directory Authentication

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More resources
EhcacheFeatureBaseMicrosoft Azure Data Explorer
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