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DBMS > Apache Impala vs. GeoMesa vs. Google Cloud Datastore vs. RDF4J vs. SAP Adaptive Server

System Properties Comparison Apache Impala vs. GeoMesa vs. Google Cloud Datastore vs. RDF4J vs. SAP Adaptive Server

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGeoMesa  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSAP Adaptive Server infoformer name: Sybase ASE  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS
Primary database modelRelational DBMSSpatial DBMSDocument storeRDF storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMS infowith Boeing's Spatial Query Server
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score35.09
Rank#25  Overall
#17  Relational DBMS
Websiteimpala.apache.orgwww.geomesa.orgcloud.google.com/­datastorerdf4j.orgwww.sap.com/­products/­technology-platform/­sybase-ase.html
Technical documentationimpala.apache.org/­impala-docs.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­datastore/­docsrdf4j.org/­documentationhelp.sap.com/­docs/­SAP_ASE
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCCRi and othersGoogleSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SAP, Sybase
Initial release20132014200820041987
Current release4.1.0, June 20225.0.0, May 202416.0
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache License 2.0commercialOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaJavaC and C++
Server operating systemsLinuxhostedLinux
OS X
Unix
Windows
AIX
HP-UX
Linux
Solaris
Unix
Windows
Data schemeyesyesschema-freeyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyes, 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.nononono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like query language (GQL)noyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
C
C++
Cobol
Java
Java
Perl
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenousing Google App EngineyesJava and Transact-SQL
TriggersnonoCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factordepending on storage layerMulti-source replication using PaxosnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistencydepending on storage layerImmediate 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 Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nodepending on storage layerno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
Apache ImpalaGeoMesaGoogle Cloud DatastoreRDF4J infoformerly known as SesameSAP Adaptive Server infoformer name: Sybase ASE
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