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DBMS > Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. ObjectBox vs. RDF4J

System Properties Comparison Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer vs. ObjectBox vs. RDF4J

Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platformExtremely fast embedded database for small devices, IoT and MobileRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedObject oriented DBMSRDF store
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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitegithub.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorerobjectbox.iordf4j.org
Technical documentationspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.iordf4j.org/­documentation
DeveloperSpotifyLeanXcaleMicrosoftObjectBox LimitedSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20142015201920172004
Current releasecloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache License 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java
Server operating systemshostedAndroid
iOS
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes 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
Secondary indexesyes infovia Elasticsearchall fields are automatically indexedyesyes
SQL infoSupport of SQLnoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Java
PHP
Python
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnoyes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and servernone
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
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAzure Active Directory Authenticationyesno
More information provided by the system vendor
HeroicLeanXcaleMicrosoft Azure Data ExplorerObjectBoxRDF4J infoformerly known as Sesame
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