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DBMS > Coveo vs. Datomic vs. Google Cloud Datastore vs. Hawkular Metrics

System Properties Comparison Coveo vs. Datomic vs. Google Cloud Datastore vs. Hawkular Metrics

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.
Primary database modelSearch engineRelational DBMSDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.11
Rank#118  Overall
#11  Search engines
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Websitewww.coveo.comwww.datomic.comcloud.google.com/­datastorewww.hawkular.org
Technical documentationdocs.coveo.comdocs.datomic.comcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperCoveoCognitectGoogleCommunity supported by Red Hat
Initial release2012201220082014
Current release1.0.7075, December 2023
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava
Server operating systemshostedAll OS with a Java VMhostedLinux
OS X
Windows
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, 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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnonoSQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
Supported programming languagesC#
Java
JavaScript
Python
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsusing Google App Engineno
TriggersyesBy using transaction functionsCallbacks using the Google Apps Engineyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesyesnone infoBut extensive use of caching in the application peersShardingSharding infobased on Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosselectable replication factor infobased on Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlgranular access controls, API key management, content filtersnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
CoveoDatomicGoogle Cloud DatastoreHawkular Metrics
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