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DBMS > Apache Impala vs. Fujitsu Enterprise Postgres vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Impala vs. Fujitsu Enterprise Postgres vs. Heroic vs. LeanXcale vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHeroic  Xexclude from comparisonLeanXcale  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.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 modelRelational DBMSRelational DBMSTime Series DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument store
Spatial DBMS
Document 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
Score0.37
Rank#278  Overall
#128  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
Websiteimpala.apache.orgwww.postgresql.fastware.comgithub.com/­spotify/­heroicwww.leanxcale.comazure.microsoft.com/­services/­data-explorer
Technical documentationimpala.apache.org/­impala-docs.htmlwww.postgresql.fastware.com/­product-manualsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySpotifyLeanXcaleMicrosoft
Initial release2013201420152019
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen 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 languageC++CJava
Server operating systemsLinuxLinux
Windows
hosted
Data schemeyesyesschema-freeyesFixed 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.nonoyes
Secondary indexesyesyesyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infothrough Apache DerbyKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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 languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsnoYes, possible languages: KQL, Python, R
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesyes 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 ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Apache ImpalaFujitsu Enterprise PostgresHeroicLeanXcaleMicrosoft Azure Data Explorer
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