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DBMS > Apache Phoenix vs. Google Cloud Datastore vs. Manticore Search vs. RDF4J

System Properties Comparison Apache Phoenix vs. Google Cloud Datastore vs. Manticore Search vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeSearch engineRDF store
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Score0.74
Rank#222  Overall
#9  RDF stores
Websitephoenix.apache.orgcloud.google.com/­datastoremanticoresearch.comrdf4j.org
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsmanual.manticoresearch.comrdf4j.org/­documentation
DeveloperApache Software FoundationGoogleManticore SoftwareSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2014200820172004
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20196.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsLinux
Unix
Windows
hostedFreeBSD
Linux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeFixed schemayes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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.nonoCan index from XML
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineuser defined functionsyes
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication using PaxosSynchronous replication based on Galera librarynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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 integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Apache PhoenixGoogle Cloud DatastoreManticore SearchRDF4J infoformerly known as Sesame
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