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DBMS > Geode vs. Informix vs. Spark SQL vs. Tkrzw

System Properties Comparison Geode vs. Informix vs. Spark SQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonInformix  Xexclude from comparisonSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.92
Rank#131  Overall
#23  Key-value stores
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegeode.apache.orgwww.ibm.com/­products/­informixspark.apache.org/­sqldbmx.net/­tkrzw
Technical documentationgeode.apache.org/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
spark.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.IBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Apache Software FoundationMikio Hirabayashi
Initial release2002198420142020
Current release1.1, February 201714.10.FC5, November 20203.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercial infofree developer edition availableOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and JavaScalaC++
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infoSince Version 12.10 support for JSON/BSON datatypesyesno
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 indexesnoyesno
SQL infoSupport of SQLSQL-like query language (OQL)yesSQL-like DML and DDL statementsno
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyesnono
Triggersyes infoCache Event Listenersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodeACIDno
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.yesyesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights per client and object definableUsers with fine-grained authentication, authorization, and auditing controlsnono

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GeodeInformixSpark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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