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DBMS > AnzoGraph DB vs. etcd vs. Google Cloud Datastore vs. Microsoft Access

System Properties Comparison AnzoGraph DB vs. etcd vs. Google Cloud Datastore vs. Microsoft Access

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)
Primary database modelGraph DBMS
RDF store
Key-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Websitecambridgesemantics.com/­anzographetcd.io
github.com/­etcd-io/­etcd
cloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­access
DeveloperCambridge SemanticsGoogleMicrosoft
Initial release201820081992
Current release2.3, January 20213.4, August 20191902 (16.0.11328.20222), March 2019
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0commercialcommercial infoBundled with Microsoft Office
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
hostedWindows infoNot a real database server, but making use of DLLs
Data schemeSchema-free and OWL/RDFS-schema supportschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes, details hereyes
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.nonono
Secondary indexesnonoyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noSQL-like query language (GQL)yes infobut not compliant to any SQL standard
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
gRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesC++
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions and aggregatesnousing Google App Engineyes infosince Access 2010 using the ACE-engine
Triggersnoyes, watching key changesCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engine
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate 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 graphsnoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction logging
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 rolesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003

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More resources
AnzoGraph DBetcdGoogle Cloud DatastoreMicrosoft Access
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