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DBMS > Blueflood vs. PlanetScale vs. ScyllaDB vs. Spark SQL

System Properties Comparison Blueflood vs. PlanetScale vs. ScyllaDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonPlanetScale  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraScalable, distributed, serverless MySQL database platform built on top of VitessCassandra and DynamoDB compatible wide column storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score1.59
Rank#151  Overall
#70  Relational DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteblueflood.ioplanetscale.comwww.scylladb.comspark.apache.org/­sql
Technical documentationgithub.com/­rax-maas/­blueflood/­wikiplanetscale.com/­docsdocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperRackspacePlanetScaleScyllaDBApache Software Foundation
Initial release2013202020152014
Current releaseScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS
Implementation languageJavaGoC++Scala
Server operating systemsLinux
OS X
Docker
Linux
macOS
LinuxLinux
OS X
Windows
Data schemepredefined schemeyesschema-freeyes
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 indexesnoyesyes infocluster global secondary indicesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statements
APIs and other access methodsHTTP RESTADO.NET
JDBC
MySQL protocol
ODBC
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoproprietary syntaxyes, Luano
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
selectable replication factor infoRepresentation of geographical distribution of servers is possiblenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency across shards
Immediate Consistency within a shard
Eventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynoyes infonot for MyISAM storage enginenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at shard levelno infoAtomicity and isolation are supported for single operationsno
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.noyesyes infoin-memory tablesno
User concepts infoAccess controlnoUsers with fine-grained authorization concept infono user groups or rolesAccess rights for users can be defined per objectno
More information provided by the system vendor
BluefloodPlanetScaleScyllaDBSpark SQL
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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BluefloodPlanetScaleScyllaDBSpark SQL
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