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DBMS > Apache Impala vs. Heroic vs. Kuzu vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Impala vs. Heroic vs. Kuzu vs. LeanXcale vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHeroic  Xexclude from comparisonKuzu  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchAn embeddable property Graph DBMS built for query speed and scalabilityA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesFully managed big data interactive analytics platform
Primary database modelRelational DBMSTime Series DBMSGraph DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument 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
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.00
Rank#402  Overall
#41  Graph DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteimpala.apache.orggithub.com/­spotify/­heroickuzudb.comwww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationimpala.apache.org/­impala-docs.htmlspotify.github.io/­heroicdocs.kuzudb.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaSpotifyLeanXcaleMicrosoft
Initial release20132014202220152019
Current release4.1.0, June 20220.4.2, May 2024cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoMIT licensecommercialcommercial
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 languageC++JavaC++
Server operating systemsLinuxserver-lesshosted
Data schemeyesschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononoyes
Secondary indexesyesyes infovia Elasticsearchnoall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
HQL (Heroic Query Language, a JSON-based language)
HTTP API
CLI Client
Cypher Query Language
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Java
JavaScript
Python
Rust
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoYes, possible languages: KQL, Python, R
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAzure Active Directory Authentication

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More resources
Apache ImpalaHeroicKuzuLeanXcaleMicrosoft Azure Data Explorer
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