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DBMS > GeoSpock vs. Google Cloud Datastore vs. PostGIS vs. Solr vs. Transbase

System Properties Comparison GeoSpock vs. Google Cloud Datastore vs. PostGIS vs. Solr vs. Transbase

Editorial information provided by DB-Engines
NameGeoSpock  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPostGIS  Xexclude from comparisonSolr  Xexclude from comparisonTransbase  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionSpatial and temporal data processing engine for extreme data scaleAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpatial extension of PostgreSQLA widely used distributed, scalable search engine based on Apache LuceneA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSDocument storeSpatial DBMSSearch engineRelational DBMS
Secondary database modelsTime Series DBMSRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score21.72
Rank#29  Overall
#1  Spatial DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitegeospock.comcloud.google.com/­datastorepostgis.netsolr.apache.orgwww.transaction.de/­en/­products/­transbase.html
Technical documentationcloud.google.com/­datastore/­docspostgis.net/­documentationsolr.apache.org/­resources.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperGeoSpockGoogleApache Software FoundationTransaction Software GmbH
Initial release2008200520061987
Current release2.0, September 20193.4.2, February 20249.6.1, May 2024Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL v2.0Open Source infoApache Version 2commercial infofree development license
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 languageJava, JavascriptCJavaC and C++
Server operating systemshostedhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infosupports customizable data types and automatic typingyes
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.nonoyesyesno
Secondary indexestemporal, categoricalyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLANSI SQL for query only (using Presto)SQL-like query language (GQL)yesSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsJava pluginsyes
TriggersnoCallbacks using the Google Apps Engineyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingyes infobased on PostgreSQLSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infobased on PostgreSQLyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
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 ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDoptimistic lockingyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononoyesno
User concepts infoAccess controlAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infobased on PostgreSQLyesfine grained access rights according to SQL-standard

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More resources
GeoSpockGoogle Cloud DatastorePostGISSolrTransbase
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