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DBMS > Apache IoTDB vs. Blueflood vs. ScyllaDB vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Blueflood vs. ScyllaDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonBlueflood  Xexclude from comparisonScyllaDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkScalable TimeSeries DBMS based on CassandraCassandra and DynamoDB compatible wide column storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSTime Series DBMSWide column storeRelational DBMS
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
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
Websiteiotdb.apache.orgblueflood.iowww.scylladb.comspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­rax-maas/­blueflood/­wikidocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationRackspaceScyllaDBApache Software Foundation
Initial release2018201320152014
Current release1.1.0, April 2023ScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license availableOpen Source infoApache 2.0
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 languageJavaJavaC++Scala
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
LinuxLinux
OS X
Windows
Data schemeyespredefined schemeschema-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.nononono
Secondary indexesyesnoyes infocluster global secondary indicesno
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
HTTP RESTProprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
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 proceduresyesnoyes, Luano
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infobased on CassandraShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor infobased on Cassandraselectable replication factor infoRepresentation of geographical distribution of servers is possiblenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono infoAtomicity and isolation are supported for single operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesnoyes infoin-memory tablesno
User concepts infoAccess controlyesnoAccess rights for users can be defined per objectno
More information provided by the system vendor
Apache IoTDBBluefloodScyllaDBSpark 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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Apache IoTDBBluefloodScyllaDBSpark SQL
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