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

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

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHarperDB  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA 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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully vectorized database across both GPUs and CPUs
Primary database modelKey-value storeRelational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#133  Overall
#23  Key-value stores
Score2.89
Rank#105  Overall
#53  Relational DBMS
Score0.55
Rank#252  Overall
#38  Document stores
Score0.69
Rank#234  Overall
#107  Relational DBMS
Websitegeode.apache.orgcloud.google.com/­spannerwww.harperdb.iowww.kinetica.com
Technical documentationgeode.apache.org/­docscloud.google.com/­spanner/­docsdocs.harperdb.io/­docsdocs.kinetica.com
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleHarperDBKinetica
Initial release2002201720172012
Current release1.1, February 20173.1, August 20217.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercialcommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC, C++
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
OS X
Linux
Data schemeschema-freeyesdynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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)yes infoQuery statements complying to ANSI 2011SQL-like data manipulation statementsSQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP 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
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnoCustom Functions infosince release 3.1user defined functions
Triggersyes infoCache Event Listenersnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication with 3 replicas for regional instances.yes infothe nodes on which a table resides can be definedSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeACID infoStrict serializable isolationAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes 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 and rolesAccess rights for users and roles on table level

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More resources
GeodeGoogle Cloud SpannerHarperDBKinetica
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