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DBMS > Drizzle vs. Google Cloud Bigtable vs. Solr vs. SurrealDB

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. Solr vs. SurrealDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSolr  Xexclude from comparisonSurrealDB  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely used distributed, scalable search engine based on Apache LuceneA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSKey-value store
Wide column store
Search engineDocument store
Graph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score42.91
Rank#24  Overall
#3  Search engines
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websitecloud.google.com/­bigtablesolr.apache.orgsurrealdb.com
Technical documentationcloud.google.com/­bigtable/­docssolr.apache.org/­resources.htmlsurrealdb.com/­docs
DeveloperDrizzle project, originally started by Brian AkerGoogleApache Software FoundationSurrealDB Ltd
Initial release2008201520062022
Current release7.2.4, September 20129.6.0, April 2024v1.1.1, January 2024
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoApache Version 2Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaRust
Server operating systemsFreeBSD
Linux
OS X
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
macOS
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesnoyes infosupports customizable data types and automatic typingyes
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.noyes
Secondary indexesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes infowith proprietary extensionsnoSolr Parallel SQL InterfaceSQL-like query language
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP/JSON API
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresnonoJava plugins
Triggersno infohooks for callbacks inside the server can be used.noyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsoptimistic lockingACID
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.noyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesyes, based on authentication and database rules

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More resources
DrizzleGoogle Cloud BigtableSolrSurrealDB
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