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

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

Editorial information provided by DB-Engines
NameAxibase  Xexclude from comparisonDatomic  Xexclude from comparisonLovefield  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationDatomic 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 platform
Primary database modelTime Series DBMSRelational DBMSRelational DBMSSearch engineRelational DBMS infocolumn oriented
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
Score0.35
Rank#282  Overall
#25  Time Series DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteaxibase.com/­docs/­atsd/­financewww.datomic.comgoogle.github.io/­lovefieldmanticoresearch.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.datomic.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAxibase CorporationCognitectGoogleManticore SoftwareMicrosoft
Initial release20132012201420172019
Current release155851.0.7075, December 20232.1.12, February 20176.0, February 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidcommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoGPL version 2commercial
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 languageJavaJava, ClojureJavaScriptC++
Server operating systemsLinuxAll OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
Linux
macOS
Windows
hosted
Data schemeyesyesyesFixed schemaFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyes infoshort, integer, long, float, double, decimal, stringyesyesInt, 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-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.nononoCan index from XMLyes
Secondary indexesnoyesyesyes infofull-text index on all search fieldsall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language infovia JavaScript builder patternSQL-like query languageKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
Proprietary protocol (Network API)
RESTful HTTP API
RESTful HTTP APIBinary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesGo
Java
PHP
Python
R
Ruby
Clojure
Java
JavaScriptElixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsnouser defined functionsYes, possible languages: KQL, Python, R
TriggersyesBy 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 nodesShardingnone 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 service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone 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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDyes infoisolated transactions for atomic changes and binary logging for safe writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes 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.yes
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 MemoryDBno
User concepts infoAccess controlnononoAzure Active Directory Authentication

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More resources
AxibaseDatomicLovefieldManticore SearchMicrosoft Azure Data Explorer
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