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DBMS > AnzoGraph DB vs. CouchDB vs. InfinityDB vs. Microsoft Azure Data Explorer vs. ReductStore

System Properties Comparison AnzoGraph DB vs. CouchDB vs. InfinityDB vs. Microsoft Azure Data Explorer vs. ReductStore

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonReductStore  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A Java embedded Key-Value Store which extends the Java Map interfaceFully managed big data interactive analytics platformDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelGraph DBMS
RDF store
Document storeKey-value storeRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsSpatial 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
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score8.30
Rank#47  Overall
#7  Document stores
Score0.08
Rank#365  Overall
#55  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websitecambridgesemantics.com/­anzographcouchdb.apache.orgboilerbay.comazure.microsoft.com/­services/­data-explorergithub.com/­reductstore
www.reduct.store
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.couchdb.org/­en/­stableboilerbay.com/­infinitydb/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerwww.reduct.store/­docs
DeveloperCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerBoiler Bay Inc.MicrosoftReductStore LLC
Initial release20182005200220192023
Current release2.3, January 20213.3.3, December 20234.0cloud service with continuous releases1.9, March 2024
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache version 2commercialcommercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJavaC++, Rust
Server operating systemsLinuxAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedDocker
Linux
macOS
Windows
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes 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.nononoyes
Secondary indexesnoyes infovia viewsno infomanual creation possible, using inversions based on multi-value capabilityall fields are automatically indexed
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.nonoKusto Query Language (KQL), SQL subset
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
RESTful HTTP/JSON APIAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP API
Supported programming languagesC++
Java
Python
C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresuser defined functions and aggregatesView functions in JavaScriptnoYes, possible languages: KQL, Python, R
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingSharding infoimproved architecture with release 2.0noneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication
Source-replica replication
noneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnono infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a single document possibleACID infoOptimistic locking for transactions; no isolation for bulk loadsno
Concurrency infoSupport for concurrent manipulation of datayesyes infostrategy: optimistic lockingyesyes
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.yesnonono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users can be defined per databasenoAzure Active Directory Authentication

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More resources
AnzoGraph DBCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"InfinityDBMicrosoft Azure Data ExplorerReductStore
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