DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DocumentDB vs. Drizzle vs. Hyprcubd vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Drizzle vs. Hyprcubd vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDrizzle  Xexclude from comparisonHyprcubd  Xexclude from comparisonSpark SQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Serverless Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbhyprcubd.com (offline)spark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDrizzle project, originally started by Brian AkerHyprcubd, Inc.Apache Software Foundation
Initial release201920082014
Current release7.2.4, September 20123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoScala
Server operating systemshostedFreeBSD
Linux
OS X
hostedLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infotime, int, uint, float, stringyes
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 indexesyesyesnono
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBCgRPC (https)JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C++
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersnono infohooks for callbacks inside the server can be used.nono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
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
none
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
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesnoyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users and rolesPluggable authentication mechanisms infoe.g. LDAP, HTTPtoken accessno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon DocumentDBDrizzleHyprcubdSpark SQL
DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

A hybrid approach for homogeneous migration to an Amazon DocumentDB elastic cluster | Amazon Web Services
4 June 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Use LangChain and vector search on Amazon DocumentDB to build a generative AI chatbot | Amazon Web Services
20 May 2024, AWS Blog

Vector search for Amazon DocumentDB (with MongoDB compatibility) is now generally available | Amazon Web Services
29 November 2023, AWS Blog

AWS announces vector search for Amazon DocumentDB
29 November 2023, AWS Blog

provided by Google News

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here