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DBMS > Elasticsearch vs. EsgynDB vs. Google Cloud Bigtable vs. IRONdb vs. ReductStore

System Properties Comparison Elasticsearch vs. EsgynDB vs. Google Cloud Bigtable vs. IRONdb vs. ReductStore

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIRONdb  Xexclude from comparisonReductStore  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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 metricEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityDesigned to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.
Primary database modelSearch engineRelational DBMSKey-value store
Wide column store
Time Series DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score132.83
Rank#7  Overall
#1  Search engines
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.05
Rank#384  Overall
#44  Time Series DBMS
Websitewww.elastic.co/­elasticsearchwww.esgyn.cncloud.google.com/­bigtablewww.circonus.com/solutions/time-series-database/github.com/­reductstore
www.reduct.store
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­bigtable/­docsdocs.circonus.com/irondb/category/getting-startedwww.reduct.store/­docs
DeveloperElasticEsgynGoogleCirconus LLC.ReductStore LLC
Initial release20102015201520172023
Current release8.6, January 2023V0.10.20, January 20181.9, March 2024
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialcommercialcommercialOpen Source infoBusiness Source License 1.1
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaC and C++C++, Rust
Server operating systemsAll OS with a Java VMLinuxhostedLinuxDocker
Linux
macOS
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes infotext, numeric, histograms
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.nononono
Secondary indexesyes infoAll search fields are automatically indexedyesnono
SQL infoSupport of SQLSQL-like query languageyesnoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP APIHTTP API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresyesJava Stored Proceduresnoyes, in Lua
Triggersyes infoby using the 'percolation' featurenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryesyesno
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 ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsno
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 integrationnonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
ElasticsearchEsgynDBGoogle Cloud BigtableIRONdbReductStore
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