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DBMS > AnzoGraph DB vs. BigObject vs. FeatureBase vs. Google Cloud Datastore

System Properties Comparison AnzoGraph DB vs. BigObject vs. FeatureBase vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonBigObject  Xexclude from comparisonFeatureBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAnalytic DBMS for real-time computations and queriesReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelGraph DBMS
RDF store
Relational DBMS infoa hierachical model (tree) can be imposedRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitecambridgesemantics.com/­anzographbigobject.iowww.featurebase.comcloud.google.com/­datastore
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.bigobject.iodocs.featurebase.comcloud.google.com/­datastore/­docs
DeveloperCambridge SemanticsBigObject, Inc.Molecula and Pilosa Open Source ContributorsGoogle
Initial release2018201520172008
Current release2.3, January 20212022, May 2022
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGo
Server operating systemsLinuxLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
macOS
hosted
Data schemeSchema-free and OWL/RDFS-schema supportyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes, details here
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.nononono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like DML and DDL statementsSQL queriesSQL-like query language (GQL)
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
fluentd
ODBC
RESTful HTTP API
gRPC
JDBC
Kafka Connector
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesLuausing Google App Engine
TriggersnononoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusternoneyesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusternoneImmediate 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.
Foreign keys infoReferential integrityno infonot needed in graphsyes infoautomatically between fact table and dimension tablesyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
Durability infoSupport for making data persistentyesyesyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
AnzoGraph DBBigObjectFeatureBaseGoogle Cloud Datastore
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