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

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

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonLMDB  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.A high performant, light-weight, embedded key-value database librarySpark 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 DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score2.09
Rank#121  Overall
#20  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websiteatoti.iowww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sqlwww.teradata.com
Technical documentationdocs.atoti.iowww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperActiveViamSymasApache Software FoundationTeradata
Initial release201120141984
Current release0.9.32, January 20243.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infofree versions availableOpen SourceOpen 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 languageJavaCScala
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
hosted
Linux
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes
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 indexesnonoyes 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 methodsJDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
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 nodesnonenoneMulti-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 integritynonoyes
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.yesyesnoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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atotiLMDBSpark SQLTeradata
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