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DBMS > Ehcache vs. Faircom DB vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Quasardb

System Properties Comparison Ehcache vs. Faircom DB vs. MarkLogic vs. Microsoft Azure Data Explorer vs. Quasardb

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Operational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformDistributed, high-performance timeseries database
Primary database modelKey-value storeKey-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedTime Series DBMS
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
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websitewww.ehcache.orgwww.faircom.com/­products/­faircom-dbwww.progress.com/­marklogicazure.microsoft.com/­services/­data-explorerquasar.ai
Technical documentationwww.ehcache.org/­documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.progress.com/­marklogic/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­master
DeveloperTerracotta Inc, owned by Software AGFairCom CorporationMarkLogic Corp.Microsoftquasardb
Initial release20091979200120192009
Current release3.10.0, March 2022V12, November 202011.0, December 2022cloud service with continuous releases3.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercial infoRestricted, free version availablecommercial inforestricted free version is availablecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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 languageJavaANSI C, C++C++C++
Server operating systemsAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
hostedBSD
Linux
OS X
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,schema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infointeger and binary
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.nonoyesyesno
Secondary indexesnoyesyesall fields are automatically indexedyes infowith tags
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsyes infoSQL92Kusto Query Language (KQL), SQL subsetSQL-like query language
APIs and other access methodsJCacheADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Supported programming languagesJava.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++yes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Rno
Triggersyes infoCache Event Listenersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta Serveryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourcetunable from ACID to Eventually ConsistentACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachYes, tunable from durable to delayed durability to in-memoryyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes, with Range Indexesnoyes infoTransient mode
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesRole-based access control at the document and subdocument levelsAzure Active Directory AuthenticationCryptographically strong user authentication and audit trail

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EhcacheFaircom DB infoformerly c-treeACEMarkLogicMicrosoft Azure Data ExplorerQuasardb
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