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DBMS > Geode vs. IRONdb vs. PlanetScale vs. Spark SQL

System Properties Comparison Geode vs. IRONdb vs. PlanetScale vs. Spark SQL

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonIRONdb  Xexclude from comparisonPlanetScale  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityScalable, distributed, serverless MySQL database platform built on top of VitessSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitegeode.apache.orgwww.circonus.com/solutions/time-series-database/planetscale.comspark.apache.org/­sql
Technical documentationgeode.apache.org/­docsdocs.circonus.com/irondb/category/getting-startedplanetscale.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Circonus LLC.PlanetScaleApache Software Foundation
Initial release2002201720202014
Current release1.1, February 2017V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++GoScala
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredLinuxDocker
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes
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.nonono
Secondary indexesnonoyesno
SQL infoSupport of SQLSQL-like query language (OQL)SQL-like query language (Circonus Analytics Query Language: CAQL)yes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes, in Luayes infoproprietary syntaxno
Triggersyes infoCache Event Listenersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationconfigurable replication factor, datacenter awareMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodenoACID at shard levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
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.yesnoyesno
User concepts infoAccess controlAccess rights per client and object definablenoUsers with fine-grained authorization concept infono user groups or rolesno

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More resources
GeodeIRONdbPlanetScaleSpark SQL
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