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DBMS > Elasticsearch vs. Google Cloud Spanner vs. Solr vs. TimescaleDB

System Properties Comparison Elasticsearch vs. Google Cloud Spanner vs. Solr vs. TimescaleDB

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Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSolr  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA 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 widely used distributed, scalable search engine based on Apache LuceneA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelSearch engineRelational DBMSSearch engineTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Spatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.elastic.co/­elasticsearchcloud.google.com/­spannersolr.apache.orgwww.timescale.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­spanner/­docssolr.apache.org/­resources.htmldocs.timescale.com
DeveloperElasticGoogleApache Software FoundationTimescale
Initial release2010201720062017
Current release8.6, January 20239.5.0, February 20242.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsAll OS with a Java VMhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyesyes
Secondary indexesyes infoAll search fields are automatically indexedyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languageyes infoQuery statements complying to ANSI 2011Solr Parallel SQL Interfaceyes infofull PostgreSQL SQL syntax
APIs and other access methodsJava 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
Java API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
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
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoJava pluginsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes infoby using the 'percolation' featurenoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication with 3 replicas for regional instances.yesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationoptimistic 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.Memcached and Redis integrationnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesfine grained access rights according to SQL-standard

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More resources
ElasticsearchGoogle Cloud SpannerSolrTimescaleDB
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