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DBMS > Apache Impala vs. Couchbase vs. Ingres vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Impala vs. Couchbase vs. Ingres vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCouchbase infoOriginally called Membase  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile databaseWell established RDBMSFully managed big data interactive analytics platform
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeKey-value store infooriginating from the former Membase product and supporting the Memcached protocol
Spatial DBMS infousing the Geocouch extension
Search engine
Time Series DBMS
Vector 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
Score16.59
Rank#36  Overall
#5  Document stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteimpala.apache.orgwww.couchbase.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorer
Technical documentationimpala.apache.org/­impala-docs.htmldocs.couchbase.comdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCouchbase, Inc.Actian CorporationMicrosoft
Initial release201320111974 infooriginally developed at University Berkely in early 1970s2019
Current release4.1.0, June 2022Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 202311.2, May 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBusiness Source License (BSL 1.1); Commercial licenses also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++, Go and ErlangC
Server operating systemsLinuxLinux
OS X
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Data schemeyesschema-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.nono infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use casesyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
Go
Java
JavaScript infoNode.js
Kotlin
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceFunctions and timers in JavaScript and UDFs in Java, Python, SQL++yesYes, possible languages: KQL, Python, R
Triggersnoyes infovia the TAP protocolyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic Shardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infoincluding cross data center replication
Source-replica replication
Ingres Replicatoryes 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 MapReduceyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency infoselectable on a per-operation basis
Immediate 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 datayesyesyes infoMVCCyes
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.noyes infoEphemeral bucketsnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosUser and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.fine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Apache ImpalaCouchbase infoOriginally called MembaseIngresMicrosoft Azure Data Explorer
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