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DBMS > EsgynDB vs. Geode vs. Spark SQL vs. Warp 10

System Properties Comparison EsgynDB vs. Geode vs. Spark SQL vs. Warp 10

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGeode  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesSpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSKey-value storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.esgyn.cngeode.apache.orgspark.apache.org/­sqlwww.warp10.io
Technical documentationgeode.apache.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperEsgynOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software FoundationSenX
Initial release2015200220142015
Current release1.1, February 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaScalaJava
Server operating systemsLinuxAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnonono
SQL infoSupport of SQLyesSQL-like query language (OQL)SQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
Java Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
All JVM based languages
C++
Groovy
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsnoyes infoWarpScript
Triggersnoyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replicationnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodenono
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.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights per client and object definablenoMandatory use of cryptographic tokens, containing fine-grained authorizations

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EsgynDBGeodeSpark SQLWarp 10
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