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DBMS > Datomic vs. Lovefield vs. Manticore Search vs. Microsoft Azure Data Explorer vs. SiteWhere

System Properties Comparison Datomic vs. Lovefield vs. Manticore Search vs. Microsoft Azure Data Explorer vs. SiteWhere

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonLovefield  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable relational database for web apps written in pure JavaScriptMulti-storage database for search, including full-text search.Fully managed big data interactive analytics platformM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryDocument 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Websitewww.datomic.comgoogle.github.io/­lovefieldmanticoresearch.comazure.microsoft.com/­services/­data-explorergithub.com/­sitewhere/­sitewhere
Technical documentationdocs.datomic.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorersitewhere1.sitewhere.io/­index.html
DeveloperCognitectGoogleManticore SoftwareMicrosoftSiteWhere
Initial release20122014201720192010
Current release1.0.6735, June 20232.1.12, February 20176.0, February 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoGPL version 2commercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaScriptC++Java
Server operating systemsAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
Linux
macOS
Windows
hostedLinux
OS X
Windows
Data schemeyesyesFixed schemaFixed schema with schema-less datatypes (dynamic)predefined scheme
Typing infopredefined data types such as float or dateyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nonoCan index from XMLyesno
Secondary indexesyesyesyes infofull-text index on all search fieldsall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP APIBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Supported programming languagesClojure
Java
JavaScriptElixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoTransaction Functionsnouser defined functionsYes, possible languages: KQL, Python, R
TriggersBy using transaction functionsUsing read-only observersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud serviceSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes infoisolated transactions for atomic changes and binary logging for safe writesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes infousing MemoryDBnono
User concepts infoAccess controlnononoAzure Active Directory AuthenticationUsers with fine-grained authorization concept

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More resources
DatomicLovefieldManticore SearchMicrosoft Azure Data ExplorerSiteWhere
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