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DBMS > Hypertable vs. MongoDB vs. Solr

System Properties Comparison Hypertable vs. MongoDB vs. Solr

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Editorial information provided by DB-Engines
NameHypertable  Xexclude from comparisonMongoDB  Xexclude from comparisonSolr  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAn open source BigTable implementation based on distributed file systems such as HadoopOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelWide column storeDocument storeSearch engine
Secondary database modelsSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score455.18
Rank#5  Overall
#1  Document stores
Score46.39
Rank#24  Overall
#3  Search engines
Websitewww.mongodb.comlucene.apache.org/­solr
Technical documentationdocs.mongodb.com/­manuallucene.apache.org/­solr/­resources.html
DeveloperHypertable Inc.MongoDB, IncApache Software Foundation
Initial release200920092006
Current release0.9.8.11, March 20166.0.1, August 20229.1.1, January 2023
License infoCommercial or Open SourceOpen Source infoGNU version 3. Commercial license availableOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenono infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or datenoyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes 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.yes
Secondary indexesrestricted infoonly exact value or prefix value scansyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoRead-only SQL queries via the MongoDB Connector for BISolr Parallel SQL Interface
APIs and other access methodsC++ API
Thrift
proprietary protocol using JSONJava API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Perl
PHP
Python
Ruby
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoJavaScriptJava plugins
Triggersnoyes infoin MongoDB Atlas onlyyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor on file system levelMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Eventual Consistency
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-document ACID Transactions with snapshot isolationoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infooptional, enabled by defaultyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-memory storage engine introduced with MongoDB version 3.2yes
User concepts infoAccess controlnoAccess rights for users and rolesyes

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