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DBMS > Amazon DocumentDB vs. Ignite vs. QuestDB vs. Solr

System Properties Comparison Amazon DocumentDB vs. Ignite vs. QuestDB vs. Solr

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonIgnite  Xexclude from comparisonQuestDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A high performance open source SQL database for time series dataA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument storeKey-value store
Relational DBMS
Time Series DBMSSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websiteaws.amazon.com/­documentdbignite.apache.orgquestdb.iosolr.apache.org
Technical documentationaws.amazon.com/­documentdb/­resourcesapacheignite.readme.io/­docsquestdb.io/­docssolr.apache.org/­resources.html
DeveloperApache Software FoundationQuestDB Technology IncApache Software Foundation
Initial release2019201520142006
Current releaseApache Ignite 2.69.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetJava (Zero-GC), C++, RustJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeyesyes infoschema-free via InfluxDB Line Protocolyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.noyesnoyes
Secondary indexesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLSQL with time-series extensionsSolr Parallel SQL Interface
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Java API
RESTful HTTP/JSON API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)noJava plugins
Triggersnoyes (cache interceptors and events)noyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes (replicated cache)Source-replica replication with eventual consistencyyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes (compute grid and hadoop accelerator)nospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual 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 operationsACIDACID for single-table writesoptimistic locking
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.yesyes infothrough memory mapped filesyes
User concepts infoAccess controlAccess rights for users and rolesSecurity Hooks for custom implementationsyes
More information provided by the system vendor
Amazon DocumentDBIgniteQuestDBSolr
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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