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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonInterbase  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 FlinkLight-weight proven RDBMS infooriginally from BorlandCassandra 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 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
Score4.61
Rank#72  Overall
#39  Relational DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.embarcadero.com/­products/­interbasewww.scylladb.comspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.embarcadero.com/­products/­interbasedocs.scylladb.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationEmbarcaderoScyllaDBApache Software Foundation
Initial release2018198420152014
Current release1.1.0, April 2023InterBase 2020, December 2019ScyllaDB Open Source 5.4.1, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen 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 languageJavaCC++Scala
Server operating systemsAll OS with a Java VM (>= 1.8)Android
iOS
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesschema-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.nono infoexport as XML data possiblenono
Secondary indexesyesyesyes infocluster global secondary indicesno
SQL infoSupport of SQLSQL-like query languageyesSQL-like DML and DDL statements (CQL)SQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
Proprietary 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
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
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 proceduresyesyes infoInterbase procedure and trigger languageyes, Luano
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingyes, 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 replicasInterbase Change Viewsselectable 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
Immediate ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno infoAtomicity and isolation are supported for single operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMultiversion concurreny controlyesyes
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.yesyesyes infoin-memory tablesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users can be defined per objectno
More information provided by the system vendor
Apache IoTDBInterbaseScyllaDBSpark 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 IoTDBInterbaseScyllaDBSpark SQL
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