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DBMS > Amazon DocumentDB vs. AnzoGraph DB vs. Google Cloud Datastore vs. Kinetica vs. searchxml

System Properties Comparison Amazon DocumentDB vs. AnzoGraph DB vs. Google Cloud Datastore vs. Kinetica vs. searchxml

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonsearchxml  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsDBMS for structured and unstructured content wrapped with an application server
Primary database modelDocument storeGraph DBMS
RDF store
Document storeRelational DBMSNative XML DBMS
Search engine
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Websiteaws.amazon.com/­documentdbcambridgesemantics.com/­anzographcloud.google.com/­datastorewww.kinetica.comwww.searchxml.net/­category/­products
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcloud.google.com/­datastore/­docsdocs.kinetica.comwww.searchxml.net/­support/­handouts
DeveloperCambridge SemanticsGoogleKineticainformationpartners gmbh
Initial release20192018200820122015
Current release2.3, January 20217.1, August 20211.0
License infoCommercial or Open Sourcecommercialcommercial infofree trial version availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C++
Server operating systemshostedLinuxhostedLinuxWindows
Data schemeschema-freeSchema-free and OWL/RDFS-schema supportschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonononoyes
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLnoSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresnouser defined functions and aggregatesusing Google App Engineuser defined functionsyes infoon the application server
TriggersnonoCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic shardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication in MPP-ClusterMulti-source replication using PaxosSource-replica replicationyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Kerberos/HDFS data loadingyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleno infonot needed in graphsyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnomultiple readers, single writer
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelDomain, group and role-based access control at the document level and for application services

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More resources
Amazon DocumentDBAnzoGraph DBGoogle Cloud DatastoreKineticasearchxml
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