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DBMS > Apache Impala vs. Ignite vs. Linter vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Impala vs. Ignite vs. Linter vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonIgnite  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.RDBMS for high security requirementsFully managed big data interactive analytics platform
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeSpatial DBMSDocument 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
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteimpala.apache.orgignite.apache.orglinter.ruazure.microsoft.com/­services/­data-explorer
Technical documentationimpala.apache.org/­impala-docs.htmlapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundationrelex.ruMicrosoft
Initial release2013201519902019
Current release4.1.0, June 2022Apache Ignite 2.6cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, Java, .NetC and C++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeyesyesyesFixed 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.noyesnoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)yes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, R
Triggersnoyes (cache interceptors and events)yesyes 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 factoryes (replicated cache)Source-replica replicationyes 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 MapReduceyes (compute grid and hadoop accelerator)noSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Apache ImpalaIgniteLinterMicrosoft Azure Data Explorer
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