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DBMS > Apache Impala vs. Hypertable vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. NuoDB

System Properties Comparison Apache Impala vs. Hypertable vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. NuoDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHypertable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNuoDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopAn open source BigTable implementation based on distributed file systems such as HadoopDistributed Event Store optimized for Internet of Things use casesFully managed big data interactive analytics platformNuoDB is a webscale distributed database that supports SQL and ACID transactions
Primary database modelRelational DBMSWide column storeEvent Store
Time Series DBMS
Relational DBMS infocolumn orientedRelational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.89
Rank#198  Overall
#92  Relational DBMS
Websiteimpala.apache.orgwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorerwww.3ds.com/­nuodb-distributed-sql-database
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorerdoc.nuodb.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHypertable Inc.IBMMicrosoftDassault Systèmes infooriginally NuoDB, Inc.
Initial release20132009201720192013
Current release4.1.0, June 20220.9.8.11, March 20162.0cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU version 3. Commercial license availablecommercial infofree developer edition availablecommercialcommercial infolimited edition free
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C and C++C++
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux infoLinux, macOS, Windows for the developer additionhostedhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesnoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nonoyesno
Secondary indexesyesrestricted infoonly exact value or prefix value scansnoall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
ODBC
C++ API
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
Perl
PHP
Python
Ruby
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesYes, possible languages: KQL, Python, RJava, SQL
Triggersnononoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoImplicit feature of the cloud servicedata is dynamically stored/cached on the nodes where it is read/written
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor on file system levelActive-active shard replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoManaged transparently by NuoDB
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID infotunable commit protocol
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes infoMVCC
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infoTemporary table
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standardAzure Active Directory AuthenticationStandard SQL roles/ privileges, Administrative Users

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More resources
Apache ImpalaHypertableIBM Db2 Event StoreMicrosoft Azure Data ExplorerNuoDB
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