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DBMS > Coveo vs. Google Cloud Datastore vs. Ingres vs. ObjectBox vs. Teradata

System Properties Comparison Coveo vs. Google Cloud Datastore vs. Ingres vs. ObjectBox vs. Teradata

Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonObjectBox  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMSExtremely fast embedded database for small devices, IoT and MobileA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelSearch engineDocument storeRelational DBMSObject oriented DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.28
Rank#114  Overall
#11  Search engines
Score4.47
Rank#76  Overall
#12  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.coveo.comcloud.google.com/­datastorewww.actian.com/­databases/­ingresobjectbox.iowww.teradata.com
Technical documentationdocs.coveo.comcloud.google.com/­datastore/­docsdocs.actian.com/­ingresdocs.objectbox.iodocs.teradata.com
DeveloperCoveoGoogleActian CorporationObjectBox LimitedTeradata
Initial release201220081974 infooriginally developed at University Berkely in early 1970s20171984
Current release11.2, May 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache License 2.0commercial
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 languageCC and C++
Server operating systemshostedhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Android
iOS
Linux
macOS
Windows
hosted
Linux
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeyesyesyes
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.nonono infobut tools for importing/exporting data from/to XML-files availablenoyes
Secondary indexesyesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoSQL-like query language (GQL)yesnoyes infoSQL 2016 + extensions
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Proprietary native 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
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyesnoyes infoUDFs, stored procedures, table functions in parallel
TriggersyesCallbacks using the Google Apps Engineyesnoyes
Partitioning methods infoMethods for storing different data on different nodesyesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynoneSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosIngres Replicatoronline/offline synchronization between client and serverMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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.Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyesyes
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.nononoyes
User concepts infoAccess controlgranular access controls, API key management, content filtersAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard
More information provided by the system vendor
CoveoGoogle Cloud DatastoreIngresObjectBoxTeradata
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