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. Apache Druid vs. Ignite vs. Infobright

System Properties Comparison Amazon DocumentDB vs. Apache Druid vs. Ignite vs. Infobright

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache Druid  Xexclude from comparisonIgnite  Xexclude from comparisonInfobright  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend
Primary database modelDocument storeRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.96
Rank#194  Overall
#91  Relational DBMS
Websiteaws.amazon.com/­documentdbdruid.apache.orgignite.apache.orgignitetech.com/­softwarelibrary/­infobrightdb
Technical documentationaws.amazon.com/­documentdb/­resourcesdruid.apache.org/­docs/­latest/­designapacheignite.readme.io/­docs
DeveloperApache Software Foundation and contributorsApache Software FoundationIgnite Technologies Inc.; formerly InfoBright Inc.
Initial release2019201220152005
Current release29.0.1, April 2024Apache Ignite 2.6
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache 2.0commercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016
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.
Implementation languageJavaC++, Java, .NetC
Server operating systemshostedLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesno infoKnowledge Grid Technology used instead
SQL infoSupport of SQLnoSQL for queryingANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes (compute grid and cache interceptors can be used instead)no
Triggersnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infomanual/auto, time-basedShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes, via HDFS, S3 or other storage enginesyes (replicated cache)Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users and rolesRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilities

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 DocumentDBApache DruidIgniteInfobright
Recent citations in the news

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

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 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

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ...
6 June 2023, Business Wire

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

provided by Google News

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

Apache Ignite: An Overview
6 September 2023, Open Source For You

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

Fire up big data processing with Apache Ignite
27 October 2016, InfoWorld

provided by Google News

Ignite Buys Database Vendor Infobright
2 May 2017, Datanami

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

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB 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

Neo4j logo

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Present your product here