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DBMS > Apache Phoenix vs. Apache Solr vs. Google Cloud Spanner vs. SurrealDB

System Properties Comparison Apache Phoenix vs. Apache Solr vs. Google Cloud Spanner vs. SurrealDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonApache Solr  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA widely used distributed, scalable search engine based on Apache LuceneA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelRelational DBMSSearch engineRelational DBMSDocument store
Graph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.82
Rank#124  Overall
#60  Relational DBMS
Score32.79
Rank#23  Overall
#3  Search engines
Score2.56
Rank#97  Overall
#50  Relational DBMS
Score1.08
Rank#176  Overall
#30  Document stores
#16  Graph DBMS
Websitephoenix.apache.orgsolr.apache.orgcloud.google.com/­spannersurrealdb.com
Technical documentationphoenix.apache.orgsolr.apache.org/­resources.htmlcloud.google.com/­spanner/­docssurrealdb.com/­docs
DeveloperApache Software FoundationApache Software FoundationGoogleSurrealDB Ltd
Initial release2014200620172022
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20199.6.1, May 2024v1.5.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2commercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaRust
Server operating systemsLinux
Unix
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)hostedLinux
macOS
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesschema-free
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesyes
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.noyesno
Secondary indexesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSolr Parallel SQL Interfaceyes infoQuery statements complying to ANSI 2011SQL-like query language
APIs and other access methodsJDBCJava API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresuser defined functionsJava pluginsno
Triggersnoyes infoUser configurable commands triggered on index changesno
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
yesMulti-source replication with 3 replicas for regional instances.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrity
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingACID infoStrict serializable isolationACID
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.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, based on authentication and database rules

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More resources
Apache PhoenixApache SolrGoogle Cloud SpannerSurrealDB
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