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DBMS > atoti vs. Hive vs. Qdrant vs. Spark SQL

System Properties Comparison atoti vs. Hive vs. Qdrant vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonHive  Xexclude from comparisonQdrant  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.data warehouse software for querying and managing large distributed datasets, built on HadoopA high-performance vector database with neural network or semantic-based matchingSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSRelational DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iohive.apache.orggithub.com/­qdrant/­qdrant
qdrant.tech
spark.apache.org/­sql
Technical documentationdocs.atoti.iocwiki.apache.org/­confluence/­display/­Hive/­Homeqdrant.tech/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamApache Software Foundation infoinitially developed by FacebookQdrantApache Software Foundation
Initial release201220212014
Current release3.1.3, April 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache 2.0
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 languageJavaJavaRustScala
Server operating systemsAll OS with a Java VMDocker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanyes
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
Secondary indexesyesyes infoKeywords, numberic ranges, geo, full-textno
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonyes infouser defined functions and integration of map-reduceno
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorCollection-level replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency, tunable consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
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.yesyesno
User concepts infoAccess controlAccess rights for users, groups and rolesKey-based authenticationno

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atotiHiveQdrantSpark SQL
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