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DBMS > Apache Impala vs. Google Cloud Datastore vs. Hive vs. RDF4J

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. Hive vs. RDF4J

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHive  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platformdata warehouse software for querying and managing large distributed datasets, built on HadoopRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelRelational DBMSDocument storeRelational DBMSRDF store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteimpala.apache.orgcloud.google.com/­datastorehive.apache.orgrdf4j.org
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docscwiki.apache.org/­confluence/­display/­Hive/­Homerdf4j.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleApache Software Foundation infoinitially developed by FacebookSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2013200820122004
Current release4.1.0, June 20223.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache 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 languageC++JavaJava
Server operating systemsLinuxhostedAll OS with a Java VMLinux
OS X
Unix
Windows
Data schemeyesschema-freeyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
PHP
Python
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineyes infouser defined functions and integration of map-reduceyes
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using Paxosselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflowyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and rolesno

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More resources
Apache ImpalaGoogle Cloud DatastoreHiveRDF4J infoformerly known as Sesame
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