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DBMS > Apache Impala vs. ArangoDB vs. Microsoft Azure Data Explorer vs. OrigoDB vs. Realm

System Properties Comparison Apache Impala vs. ArangoDB vs. Microsoft Azure Data Explorer vs. OrigoDB vs. Realm

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonArangoDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrigoDB  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopNative multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language.Fully managed big data interactive analytics platformA fully ACID in-memory object graph databaseA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Search engine
Relational DBMS infocolumn orientedDocument store
Object oriented DBMS
Document store
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
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.26
Rank#88  Overall
#15  Document stores
#5  Graph DBMS
#12  Key-value stores
#10  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websiteimpala.apache.orgarangodb.comazure.microsoft.com/­services/­data-explorerorigodb.comrealm.io
Technical documentationimpala.apache.org/­impala-docs.htmldocs.arangodb.comdocs.microsoft.com/­en-us/­azure/­data-explorerorigodb.com/­docsrealm.io/­docs
Social network pagesLinkedInTwitterYouTubeFacebookInstagram
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaArangoDB Inc.MicrosoftRobert Friberg et alRealm, acquired by MongoDB in May 2019
Initial release2013201220192009 infounder the name LiveDB2014
Current release4.1.0, June 20223.11.5, November 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; Commercial license (Enterprise) availablecommercialOpen SourceOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour.
Implementation languageC++C++C#
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
Windows
Android
Backend: server-less
iOS
Windows
Data schemeyesschema-free infoautomatically recognizes schema within a collectionFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes infostring, double, boolean, list, hashyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETno
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
ODBC
AQL
Foxx Framework
Graph API (Gremlin)
GraphQL query language
HTTP API
Java & SpringData
JSON style queries
VelocyPack/VelocyStream
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP API
LINQ
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Clojure
Elixir
Go
Java
JavaScript (Node.js)
PHP
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJavaScriptYes, possible languages: KQL, Python, Ryesno inforuns within the applications so server-side scripts are unnecessary
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoDomain Eventsyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infosince version 2.0Sharding infoImplicit feature of the cloud servicehorizontal partitioning infoclient side managed; servers are not synchronizednone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication with configurable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno infocan be done with stored procedures in JavaScriptSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoconfigurable per collection or per write
Immediate Consistency
OneShard (highly available, fault-tolerant deployment mode with ACID semantics)
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsnodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoIn-Memory realm
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesAzure Active Directory AuthenticationRole based authorizationyes
More information provided by the system vendor
Apache ImpalaArangoDBMicrosoft Azure Data ExplorerOrigoDBRealm
Specific characteristicsGraph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading...
» more
Competitive advantagesConsolidation: As a native multi-model database, can be used as a full blown document...
» more
Typical application scenariosNative multi-model in ArangoDB is being used for a broad range of projects across...
» more
Key customersCisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,...
» more
Market metricsArangoDB is the leading native multi-model database with over 11,000 stargazers on...
» more
Licensing and pricing modelsVery permissive Apache 2 License for Community Edition & commercial licenses are...
» more

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Apache ImpalaArangoDBMicrosoft Azure Data ExplorerOrigoDBRealm
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