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DBMS > Amazon DocumentDB vs. KeyDB vs. Spark SQL vs. YugabyteDB

System Properties Comparison Amazon DocumentDB vs. KeyDB vs. Spark SQL vs. YugabyteDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonKeyDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonYugabyteDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsSpark SQL is a component on top of 'Spark Core' for structured data processingHigh-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.
Primary database modelDocument storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.91
Rank#102  Overall
#51  Relational DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­Snapchat/­KeyDB
keydb.dev
spark.apache.org/­sqlwww.yugabyte.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.keydb.devspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.yugabyte.com
github.com/­yugabyte/­yugabyte-db
DeveloperEQ Alpha Technology Ltd.Apache Software FoundationYugabyte Inc.
Initial release2019201920142017
Current release3.5.0 ( 2.13), September 20232.19, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.
Implementation languageC++ScalaC and C++
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
OS X
Data schemeschema-freeschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesyes
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.nononono
Secondary indexesyesyes infoby using the Redis Search modulenoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes, PostgreSQL compatible
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)Proprietary protocol infoRESP - REdis Serialization ProtocoJDBC
ODBC
JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Java
Python
R
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoLuanoyes infosql, plpgsql, C
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark CoreHash and Range Sharding, row-level geo-partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication
Source-replica replication
noneBased on Raft distributed consensus protocol, minimum 3 replicas for continuous availability
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Strong consistency on writes and tunable consistency on reads
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsOptimistic locking, atomic execution of commands blocks and scriptsnoDistributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes infobased on RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and rolessimple password-based access control and ACLnoyes
More information provided by the system vendor
Amazon DocumentDBKeyDBSpark SQLYugabyteDB
Specific characteristicsYugabyteDB is an open source distributed SQL database for cloud native transactional...
» more
Competitive advantagesPostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more
Typical application scenariosSystems of record and engagement for cloud native applications that require resilience,...
» more
Market metrics2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more
Licensing and pricing modelsApache 2.0 license for the database
» more

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More resources
Amazon DocumentDBKeyDBSpark SQLYugabyteDB
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