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DBMS > Geode vs. Google Cloud Datastore vs. Google Cloud Spanner vs. Kinetica

System Properties Comparison Geode vs. Google Cloud Datastore vs. Google Cloud Spanner vs. Kinetica

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Fully vectorized database across both GPUs and CPUs
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score4.36
Rank#72  Overall
#12  Document stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitegeode.apache.orgcloud.google.com/­datastorecloud.google.com/­spannerwww.kinetica.com
Technical documentationgeode.apache.org/­docscloud.google.com/­datastore/­docscloud.google.com/­spanner/­docsdocs.kinetica.com
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleGoogleKinetica
Initial release2002200820172012
Current release1.1, February 20177.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedhostedLinux
Data schemeschema-freeschema-freeyesyes
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.nononono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLSQL-like query language (OQL)SQL-like query language (GQL)yes infoQuery statements complying to ANSI 2011SQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsusing Google App Enginenouser defined functions
Triggersyes infoCache Event ListenersCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication using PaxosMulti-source replication with 3 replicas for regional instances.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes infousing Google Cloud Dataflowno
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.Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table level

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GeodeGoogle Cloud DatastoreGoogle Cloud SpannerKinetica
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