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DBMS > atoti vs. Firebase Realtime Database vs. Qdrant vs. Spark SQL

System Properties Comparison atoti vs. Firebase Realtime Database vs. Qdrant vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonFirebase Realtime Database  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.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest 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 processing
Primary database modelObject oriented DBMSDocument storeVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score13.64
Rank#39  Overall
#6  Document stores
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iofirebase.google.com/­products/­realtime-databasegithub.com/­qdrant/­qdrant
qdrant.tech
spark.apache.org/­sql
Technical documentationdocs.atoti.iofirebase.google.com/­docs/­databaseqdrant.tech/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamGoogle infoacquired by Google 2014QdrantApache Software Foundation
Initial release201220212014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustScala
Server operating systemshostedDocker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-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.nonono
Secondary indexesyesyes infoKeywords, numberic ranges, geo, full-textno
SQL infoSupport of SQLMultidimensional Expressions (MDX)nonoSQL-like DML and DDL statements
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
Supported programming languagesJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonlimited functionality with using 'rules'no
TriggersCallbacks are triggered when data changesno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesCollection-level replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency, tunable consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesno
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 controlyes, based on authentication and database rulesKey-based authenticationno

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More resources
atotiFirebase Realtime DatabaseQdrantSpark SQL
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