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DBMS > Databend vs. PouchDB vs. Spark SQL vs. Warp 10

System Properties Comparison Databend vs. PouchDB vs. Spark SQL vs. Warp 10

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityJavaScript DBMS with an API inspired by CouchDBSpark 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 DBMSDocument storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
pouchdb.comspark.apache.org/­sqlwww.warp10.io
Technical documentationdocs.databend.compouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperDatabend LabsApache Software FoundationApache Software FoundationSenX
Initial release2021201220142015
Current release1.0.59, April 20237.1.1, June 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen 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 languageRustJavaScriptScalaJava
Server operating systemshosted
Linux
macOS
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesnoyes infovia viewsnono
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsno
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
JavaScriptJava
Python
R
Scala
Server-side scripts infoStored proceduresnoView functions in JavaScriptnoyes infoWarpScript
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesnonoMandatory use of cryptographic tokens, containing fine-grained authorizations

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DatabendPouchDBSpark SQLWarp 10
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