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DBMS > Apache Impala vs. Microsoft Azure Data Explorer vs. STSdb vs. Vertica

System Properties Comparison Apache Impala vs. Microsoft Azure Data Explorer vs. STSdb vs. Vertica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFully managed big data interactive analytics platformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSRelational DBMS infocolumn orientedKey-value storeRelational 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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteimpala.apache.orgazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201920112005
Current release4.1.0, June 2022cloud service with continuous releases4.0.8, September 201512.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#C++
Server operating systemsLinuxhostedWindowsLinux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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-typesyes infoprimitive types and user defined types (classes)yes
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 indexesyesall fields are automatically indexednoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Rnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAzure Active Directory Authenticationnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache ImpalaMicrosoft Azure Data ExplorerSTSdbVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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Apache ImpalaMicrosoft Azure Data ExplorerSTSdbVertica infoOpenText™ Vertica™
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