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DBMS > Hawkular Metrics vs. Memcached vs. Microsoft Azure Data Explorer vs. Stardog vs. TimesTen

System Properties Comparison Hawkular Metrics vs. Memcached vs. Microsoft Azure Data Explorer vs. Stardog vs. TimesTen

Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonStardog  Xexclude from comparisonTimesTen  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.In-memory key-value store, originally intended for cachingFully managed big data interactive analytics platformEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationAn in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.
Primary database modelTime Series DBMSKey-value storeRelational DBMS infocolumn orientedGraph DBMS
RDF store
Relational 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
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score16.84
Rank#32  Overall
#4  Key-value stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Score1.26
Rank#164  Overall
#75  Relational DBMS
Websitewww.hawkular.orgwww.memcached.orgazure.microsoft.com/­services/­data-explorerwww.stardog.comwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidegithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­en-us/­azure/­data-explorerdocs.stardog.comdocs.oracle.com/­en/­database/­other-databases/­timesten/­index.html
DeveloperCommunity supported by Red HatDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftStardog-UnionOracle infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20142003201920101998
Current release1.6.29, June 2024cloud service with continuous releases7.3.0, May 2020Release 22.1
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoBSD licensecommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCJava
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
OS X
Unix
Windows
hostedLinux
macOS
Windows
IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesnoyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.noyesno infoImport/export of XML data possibleno
Secondary indexesnonoall fields are automatically indexedyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes
APIs and other access methodsHTTP RESTProprietary protocolMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC
Supported programming languagesGo
Java
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
C
C++
Java
Node.js
PL/SQL
Python
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Ruser defined functions and aggregates, HTTP Server extensions in JavaPL/SQL
Triggersyes infovia Hawkular Alertingnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handlersno
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandranoneSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandranone infoRepcached, a Memcached patch, provides this functionallityyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication in HA-ClusterMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Immediate Consistency in HA-ClusterImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes inforelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnoyes infousing SASL (Simple Authentication and Security Layer) protocolAzure Active Directory AuthenticationAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Hawkular MetricsMemcachedMicrosoft Azure Data ExplorerStardogTimesTen
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