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DBMS > AnzoGraph DB vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. Teradata Aster

System Properties Comparison AnzoGraph DB vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. Teradata Aster

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionScalable 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 PlatformDatabase as a Service offering with high compatibility to Microsoft SQL ServerPlatform for big data analytics on multistructured data sources and types
Primary database modelGraph DBMS
RDF store
Document storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score4.49
Rank#79  Overall
#12  Document stores
Score78.40
Rank#15  Overall
#10  Relational DBMS
Websitecambridgesemantics.com/­anzographcloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperCambridge SemanticsGoogleMicrosoftTeradata
Initial release2018200820102005
Current release2.3, January 2021V12
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemsLinuxhostedhostedLinux
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes, 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.nonoyesyes infoin Aster File Store
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like query language (GQL)yesyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App EngineTransact SQLR packages
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterMulti-source replication using Paxosyes, with always 3 replicas availableyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infonot needed in graphsyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
AnzoGraph DBGoogle Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureTeradata Aster
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