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DBMS > atoti vs. Qdrant vs. Spark SQL vs. TDSQL for MySQL

System Properties Comparison atoti vs. Qdrant vs. Spark SQL vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonQdrant  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A high-performance vector database with neural network or semantic-based matchingSpark SQL is a component on top of 'Spark Core' for structured data processingA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelObject oriented DBMSVector DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.85
Rank#207  Overall
#97  Relational DBMS
Websiteatoti.iogithub.com/­qdrant/­qdrant
qdrant.tech
spark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdb
Technical documentationdocs.atoti.ioqdrant.tech/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042
DeveloperActiveViamQdrantApache Software FoundationTencent
Initial release202120142013
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustScala
Server operating systemsDocker
Linux
macOS
Windows
Linux
OS X
Windows
hosted
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateNumbers, Strings, Geo, Booleanyesyes
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.nonono
Secondary indexesyes infoKeywords, numberic ranges, geo, full-textnoyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like DML and DDL statementsyes
APIs and other access methodsgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresPythonnoyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark CoreAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesCollection-level replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency, tunable consistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
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.yesyesnono
User concepts infoAccess controlKey-based authenticationnoUsers with fine-grained authorization concept

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More resources
atotiQdrantSpark SQLTDSQL for MySQL
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