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DBMS > CockroachDB vs. Drizzle vs. Lovefield vs. Solr

System Properties Comparison CockroachDB vs. Drizzle vs. Lovefield vs. Solr

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonDrizzle  Xexclude from comparisonLovefield  Xexclude from comparisonSolr  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.
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Embeddable relational database for web apps written in pure JavaScriptA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.cockroachlabs.comgoogle.github.io/­lovefieldsolr.apache.org
Technical documentationwww.cockroachlabs.com/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsolr.apache.org/­resources.html
DeveloperCockroach LabsDrizzle project, originally started by Brian AkerGoogleApache Software Foundation
Initial release2015200820142006
Current release24.1.0, May 20247.2.4, September 20122.1.12, February 20179.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availableOpen Source infoGNU GPLOpen Source infoApache 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++JavaScriptJava
Server operating systemsLinux
macOS
Windows
FreeBSD
Linux
OS X
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemedynamic schemayesyesyes 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.nonoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes, wire compatible with PostgreSQLyes infowith proprietary extensionsSQL-like query language infovia JavaScript builder patternSolr Parallel SQL Interface
APIs and other access methodsJDBCJDBCJava API
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C
C++
Java
PHP
JavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnononoJava plugins
Triggersnono infohooks for callbacks inside the server can be used.Using read-only observersyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication
Source-replica replication
noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing MemoryDByes
User concepts infoAccess controlRole-based access controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnoyes

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More resources
CockroachDBDrizzleLovefieldSolr
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