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DBMS > atoti vs. FeatureBase vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison atoti vs. FeatureBase vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonFeatureBase  Xexclude from comparisonHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Time 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 platform
Primary database modelObject oriented DBMSRelational DBMSTime Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
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
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
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
Websiteatoti.iowww.featurebase.comgithub.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.atoti.iodocs.featurebase.comspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperActiveViamMolecula and Pilosa Open Source ContributorsSpotifyLeanXcaleMicrosoft
Initial release2017201420152019
Current release2022, May 2022cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache 2.0commercialcommercial
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 languageJavaGoJava
Server operating systemsLinux
macOS
hosted
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes 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.nonoyes
Secondary indexesnoyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL queriesnoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsgRPC
JDBC
Kafka Connector
ODBC
HQL (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
Supported programming languagesJava
Python
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresPythonnoYes, possible languages: KQL, Python, R
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyesyes
Durability infoSupport for making data persistentyes, using Linux fsyncyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesno
User concepts infoAccess controlAzure Active Directory Authentication

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More resources
atotiFeatureBaseHeroicLeanXcaleMicrosoft Azure Data Explorer
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