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DBMS > AgensGraph vs. Google Cloud Datastore vs. Solr vs. Teradata

System Properties Comparison AgensGraph vs. Google Cloud Datastore vs. Solr vs. Teradata

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSolr  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely used distributed, scalable search engine based on Apache LuceneA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelGraph DBMS
Relational DBMS
Document storeSearch engineRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score42.91
Rank#24  Overall
#3  Search engines
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitebitnine.net/­agensgraphcloud.google.com/­datastoresolr.apache.orgwww.teradata.com
Technical documentationbitnine.net/­documentationcloud.google.com/­datastore/­docssolr.apache.org/­resources.htmldocs.teradata.com
DeveloperBitnine Global Inc.GoogleApache Software FoundationTeradata
Initial release2016200820061984
Current release2.1, December 20189.6.0, April 2024Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)hosted
Linux
Data schemedepending on used data modelschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes, details hereyes infosupports customizable data types and automatic typingyes
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
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesSQL-like query language (GQL)Solr Parallel SQL Interfaceyes infoSQL 2016 + extensions
APIs and other access methodsCypher Query Language
JDBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyesusing Google App EngineJava pluginsyes infoUDFs, stored procedures, table functions in parallel
TriggersnoCallbacks using the Google Apps Engineyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication using PaxosyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsoptimistic lockingACID
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.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesfine grained access rights according to SQL-standard

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More resources
AgensGraphGoogle Cloud DatastoreSolrTeradata
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