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DBMS > Apache Impala vs. CouchDB vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak TS

System Properties Comparison Apache Impala vs. CouchDB vs. Ignite vs. Microsoft Azure Data Explorer vs. Riak TS

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRiak TS  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformRiak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelRelational DBMSDocument storeKey-value store
Relational DBMS
Relational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsDocument storeSpatial DBMS infousing the Geocouch extensionDocument 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
Score9.30
Rank#45  Overall
#7  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.20
Rank#319  Overall
#27  Time Series DBMS
Websiteimpala.apache.orgcouchdb.apache.orgignite.apache.orgazure.microsoft.com/­services/­data-explorer
Technical documentationimpala.apache.org/­impala-docs.htmldocs.couchdb.org/­en/­stableapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerApache Software FoundationMicrosoftOpen Source, formerly Basho Technologies
Initial release20132005201520192015
Current release4.1.0, June 20223.3.3, December 2023Apache Ignite 2.6cloud service with continuous releases3.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache version 2Open Source infoApache 2.0commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ErlangC++, Java, .NetErlang
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
hostedLinux
OS X
Data schemeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
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-typesno
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.nonoyesyesno
Secondary indexesyesyes infovia viewsyesall fields are automatically indexedrestricted
SQL infoSupport of SQLSQL-like DML and DDL statementsnoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetyes, limited
APIs and other access methodsJDBC
ODBC
RESTful HTTP/JSON APIHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceView functions in JavaScriptyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, RErlang
Triggersnoyesyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoimproved architecture with release 2.0ShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
yes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonononono infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoatomic operations within a single document possibleACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsAzure Active Directory Authenticationno

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Apache ImpalaCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"IgniteMicrosoft Azure Data ExplorerRiak TS
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