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

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

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonPlanetScale  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable, distributed, serverless MySQL database platform built on top of VitessSpark 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 DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.49
Rank#155  Overall
#72  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.esgyn.cnplanetscale.comspark.apache.org/­sqlwww.warp10.io
Technical documentationplanetscale.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperEsgynPlanetScaleApache Software FoundationSenX
Initial release2015202020142015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaGoScalaJava
Server operating systemsLinuxDocker
Linux
macOS
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesyesschema-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.nonono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
MySQL protocol
ODBC
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetAda
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 proceduresJava Stored Proceduresyes infoproprietary syntaxnoyes infoWarpScript
Triggersnoyesnono
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 replication
Source-replica replication
noneselectable 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 Consistency across shards
Immediate Consistency within a shard
Immediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesyes infonot for MyISAM storage enginenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at shard levelnono
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyesyes
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-standardUsers with fine-grained authorization concept infono user groups or rolesnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
EsgynDBPlanetScaleSpark SQLWarp 10
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