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DBMS > atoti vs. ObjectBox vs. Spark SQL vs. Teradata

System Properties Comparison atoti vs. ObjectBox vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonObjectBox  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Extremely fast embedded database for small devices, IoT and MobileSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelObject oriented DBMSObject oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.59
Rank#242  Overall
#10  Object oriented DBMS
Score1.22
Rank#172  Overall
#5  Object oriented DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score47.84
Rank#21  Overall
#15  Relational DBMS
Websiteatoti.ioobjectbox.iospark.apache.org/­sqlwww.teradata.com
Technical documentationdocs.atoti.iodocs.objectbox.iospark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperActiveViamObjectBox LimitedApache Software FoundationTeradata
Initial release201720141984
Current release3.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache License 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++Scala
Server operating systemsAndroid
iOS
Linux
macOS
Windows
Linux
OS X
Windows
hosted
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes
Secondary indexesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsProprietary native APIJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresPythonnonoyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesonline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesnofine grained access rights according to SQL-standard
More information provided by the system vendor
atotiObjectBoxSpark SQLTeradata
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