DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DocumentDB vs. DolphinDB vs. EXASOL vs. Google Cloud Firestore vs. WakandaDB

System Properties Comparison Amazon DocumentDB vs. DolphinDB vs. EXASOL vs. Google Cloud Firestore vs. WakandaDB

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.High-performance, in-memory, MPP database specifically designed for in-memory analytics.Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument storeTime Series DBMSRelational DBMSDocument storeObject oriented DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score7.36
Rank#53  Overall
#9  Document stores
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websiteaws.amazon.com/­documentdbwww.dolphindb.comwww.exasol.comfirebase.google.com/­products/­firestorewakanda.github.io
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.dolphindb.cn/­en/­help200/­index.htmlwww.exasol.com/­resourcesfirebase.google.com/­docs/­firestorewakanda.github.io/­doc
DeveloperDolphinDB, IncExasolGoogleWakanda SAS
Initial release20192018200020172012
Current releasev2.00.4, January 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infofree community version availablecommercialcommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, JavaScript
Server operating systemshostedLinux
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query languageyesnono
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
.Net
JDBC
ODBC
WebSocket
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
Lua
Python
R
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
JavaScript
Server-side scripts infoStored proceduresnoyesuser defined functionsyes, Firebase Rules & Cloud Functionsyes
Triggersnonoyesyes, with Cloud Functionsyes
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyes infoHadoop integrationUsing Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsyesACIDyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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 and rolesAdministrators, Users, GroupsAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.yes

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 DocumentDBDolphinDBEXASOLGoogle Cloud FirestoreWakandaDB
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

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 Amazon DocumentDB I/O-Optimized
21 November 2023, AWS Blog

Use headless clusters in Amazon DocumentDB for cost-effective multi-Region resiliency | Amazon Web Services
8 March 2024, AWS Blog

provided by Google News

It's Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
14 May 2024, insideBIGDATA

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series
21 May 2024, Unite.AI

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Exasol Unveils New Suite of AI Tools to Turbocharge Enterprise Data Analytics
22 February 2024, AiThority

provided by Google News

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

Google's Cloud-Native NoSQL Database Cloud Firestore Is Now Generally Available
8 February 2019, InfoQ.com

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

provided by Google News



Share this page

Featured Products

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

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.

Present your product here