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DBMS > Cloudflare Workers KV vs. HBase vs. QuestDB vs. Spark SQL vs. SwayDB

System Properties Comparison Cloudflare Workers KV vs. HBase vs. QuestDB vs. Spark SQL vs. SwayDB

Editorial information provided by DB-Engines
NameCloudflare Workers KV  Xexclude from comparisonHBase  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionA global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.Wide-column store based on Apache Hadoop and on concepts of BigTableA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelKey-value storeWide column storeTime Series DBMSRelational DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#283  Overall
#40  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.00
Rank#382  Overall
#59  Key-value stores
Websitewww.cloudflare.com/­developer-platform/­workers-kvhbase.apache.orgquestdb.iospark.apache.org/­sqlswaydb.simer.au
Technical documentationdevelopers.cloudflare.com/­kv/­apihbase.apache.org/­book.htmlquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCloudflareApache Software Foundation infoApache top-level project, originally developed by PowersetQuestDB Technology IncApache Software FoundationSimer Plaha
Initial release20182008201420142018
Current release2.3.4, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava (Zero-GC), C++, RustScalaScala
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleyes infoschema-free via InfluxDB Line Protocolyesschema-free
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROyesyesno
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.nonononono
Secondary indexesnonononono
SQL infoSupport of SQLnonoSQL with time-series extensionsSQL-like DML and DDL statementsno
APIs and other access methodsHTTP REST
Proprietary protocol
Java API
RESTful HTTP API
Thrift
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javanonono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)yes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Source-replica replication with eventual consistencynonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACID for single-table writesnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infothrough memory mapped filesnoyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono
More information provided by the system vendor
Cloudflare Workers KVHBaseQuestDBSpark SQLSwayDB
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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