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DBMS > Amazon CloudSearch vs. Google Cloud Datastore vs. Newts vs. Teradata vs. Teradata Aster

System Properties Comparison Amazon CloudSearch vs. Google Cloud Datastore vs. Newts vs. Teradata vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonNewts  Xexclude from comparisonTeradata  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.
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformTime Series DBMS based on CassandraA hybrid cloud data analytics software platform (Teradata Vantage)Platform for big data analytics on multistructured data sources and types
Primary database modelSearch engineDocument storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websiteaws.amazon.com/­cloudsearchcloud.google.com/­datastoreopennms.github.io/­newtswww.teradata.com
Technical documentationdocs.aws.amazon.com/­cloudsearchcloud.google.com/­datastore/­docsgithub.com/­OpenNMS/­newts/­wikidocs.teradata.com
DeveloperAmazonGoogleOpenNMS GroupTeradataTeradata
Initial release20122008201419842005
Current releaseTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedLinux
OS X
Windows
hosted
Linux
Linux
Data schemeyesschema-freeschema-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 dateyesyes, details hereyesyesyes
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 indexesyes infoall search fields are automatically indexedyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLnoSQL-like query language (GQL)noyes infoSQL 2016 + extensionsyes
APIs and other access methodsHTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
Java API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnousing Google App Enginenoyes infoUDFs, stored procedures, table functions in parallelR packages
TriggersnoCallbacks using the Google Apps Enginenoyesno
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding infobased on CassandraSharding infoHashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSMulti-source replication using Paxosselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
yes 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 methodsnoyes infousing Google Cloud Dataflownonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACIDACID
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.nonoyesno
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Amazon CloudSearchGoogle Cloud DatastoreNewtsTeradataTeradata Aster
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