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DBMS > Blueflood vs. ScyllaDB vs. Spark SQL vs. Splice Machine

System Properties Comparison Blueflood vs. ScyllaDB vs. Spark SQL vs. Splice Machine

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Editorial information provided by DB-Engines
NameBlueflood  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable TimeSeries DBMS based on CassandraCassandra and DynamoDB compatible wide column storeSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#353  Overall
#34  Time Series DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteblueflood.iowww.scylladb.comspark.apache.org/­sqlsplicemachine.com
Technical documentationgithub.com/­rax-maas/­blueflood/­wikidocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperRackspaceScyllaDBApache Software FoundationSplice Machine
Initial release2013201520142014
Current releaseScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaC++ScalaJava
Server operating systemsLinux
OS X
LinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemepredefined schemeschema-freeyesyes
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 indexesnoyes infocluster global secondary indicesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statementsyes
APIs and other access methodsHTTP RESTProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesFor 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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes, Luanoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandraselectable replication factor infoRepresentation of geographical distribution of servers is possiblenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoAtomicity and isolation are supported for single operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyes infoin-memory tablesnoyes
User concepts infoAccess controlnoAccess rights for users can be defined per objectnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
BluefloodScyllaDBSpark SQLSplice Machine
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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BluefloodScyllaDBSpark SQLSplice Machine
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