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DBMS > Badger vs. Elasticsearch vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

System Properties Comparison Badger vs. Elasticsearch vs. Google Cloud Firestore vs. HugeGraph vs. IRONdb

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHugeGraph  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A 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 metricCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.A fast-speed and highly-scalable Graph DBMSA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelKey-value storeSearch engineDocument storeGraph DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score132.83
Rank#7  Overall
#1  Search engines
Score7.36
Rank#53  Overall
#9  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websitegithub.com/­dgraph-io/­badgerwww.elastic.co/­elasticsearchfirebase.google.com/­products/­firestoregithub.com/­hugegraph
hugegraph.apache.org
www.circonus.com/solutions/time-series-database/
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­firestorehugegraph.apache.org/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperDGraph LabsElasticGoogleBaiduCirconus LLC.
Initial release20172010201720182017
Current release8.6, January 20230.9V0.10.20, January 2018
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoElastic LicensecommercialOpen Source infoApache Version 2.0commercial
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 languageGoJavaJavaC and C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedLinux
macOS
Unix
Linux
Data schemeschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyesyesyes 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.nonononono
Secondary indexesnoyes infoAll search fields are automatically indexedyesyes infoalso supports composite index and range indexno
SQL infoSupport of SQLnoSQL-like query languagenonoSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
HTTP API
Supported programming languagesGo.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
Groovy
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoyesyes, Firebase Rules & Cloud Functionsasynchronous Gremlin script jobsyes, in Lua
Triggersnoyes infoby using the 'percolation' featureyes, with Cloud Functionsnono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replicationyes infodepending on used storage backend, e.g. Cassandra and HBaseconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop ConnectorUsing Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Users, roles and permissionsno

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More resources
BadgerElasticsearchGoogle Cloud FirestoreHugeGraphIRONdb
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