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DBMS > Apache Impala vs. Drizzle vs. Microsoft Azure Data Explorer vs. TimescaleDB

System Properties Comparison Apache Impala vs. Drizzle vs. Microsoft Azure Data Explorer vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn orientedTime Series DBMS
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
Relational 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
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteimpala.apache.orgazure.microsoft.com/­services/­data-explorerwww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerMicrosoftTimescale
Initial release2013200820192017
Current release4.1.0, June 20227.2.4, September 2012cloud service with continuous releases2.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
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-typesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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.noyesyes
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsKusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
JDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoYes, possible languages: KQL, Python, Ruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnono infohooks for callbacks inside the server can be used.yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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 KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Apache ImpalaDrizzleMicrosoft Azure Data ExplorerTimescaleDB
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