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

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

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonInterbase  Xexclude from comparisonOceanBase  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 BorlandA distributed, high available RDBMS compatible with Oracle and MySQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Wide column 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
Score1.66
Rank#147  Overall
#68  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgwww.embarcadero.com/­products/­interbaseen.oceanbase.comspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.embarcadero.com/­products/­interbaseen.oceanbase.com/­docs/­oceanbase-databasespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationEmbarcaderoOceanBase infopreviously Alibaba and Ant GroupApache Software Foundation
Initial release2018198420102014
Current release1.1.0, April 2023InterBase 2020, December 20194.3.0, April 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoCommercial 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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Implementation languageJavaCC++Scala
Server operating systemsAll OS with a Java VM (>= 1.8)Android
iOS
Linux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyesyes
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 possibleyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageyesyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
Ada infoin MySQL-compatible model
C infoin Oracle- and MySQL- compatible models
C++ infoin Oracle- and MySQL- compatible models
D infoin MySQL-compatible model
Delphi infoin MySQL-compatible model
Eiffel infoin MySQL-compatible model
Erlang infoin MySQL-compatible model
Haskell infoin MySQL-compatible model
Java infoin Oracle- and MySQL- compatible models
JavaScript (Node.js) infoin MySQL-compatible model
Objective-C infoin MySQL-compatible model
OCaml infoin MySQL-compatible model
Perl infoin MySQL-compatible model
PHP infoin MySQL-compatible model
Python infoin MySQL-compatible model
Ruby infoin MySQL-compatible model
Scheme infoin MySQL-compatible model
Tcl infoin MySQL-compatible model
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes infoInterbase procedure and trigger languagePL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible modeno
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)nonehorizontal partitioning (by hash, key, range, range columns, list, and list columns)yes, 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 ViewsMulti-source replication using Paxosnone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.yesyesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache IoTDBInterbaseOceanBaseSpark SQL
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