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DBMS > Elasticsearch vs. Firebase Realtime Database vs. Hawkular Metrics vs. Milvus vs. Oracle Berkeley DB

System Properties Comparison Elasticsearch vs. Firebase Realtime Database vs. Hawkular Metrics vs. Milvus vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMilvus  Xexclude from comparisonOracle Berkeley DB  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 metricCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A DBMS designed for efficient storage of vector data and vector similarity searchesWidely used in-process key-value store
Primary database modelSearch engineDocument storeTime Series DBMSVector DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score14.29
Rank#39  Overall
#6  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitewww.elastic.co/­elasticsearchfirebase.google.com/­products/­realtime-databasewww.hawkular.orgmilvus.iowww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlfirebase.google.com/­docs/­databasewww.hawkular.org/­hawkular-metrics/­docs/­user-guidemilvus.io/­docs/­overview.mddocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperElasticGoogle infoacquired by Google 2014Community supported by Red HatOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20102012201420191994
Current release8.6, January 20232.3.4, January 202418.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaJavaC++, GoC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesVector, Numeric and Stringno
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.nonononoyes infoonly with the Berkeley DB XML edition
Secondary indexesyes infoAll search fields are automatically indexedyesnonoyes
SQL infoSupport of SQLSQL-like query languagenononoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJava API
RESTful HTTP/JSON API
Android
iOS
JavaScript API
RESTful HTTP API
HTTP RESTRESTful HTTP API
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
Java
JavaScript
Objective-C
Go
Java
Python
Ruby
C++
Go
Java
JavaScript (Node.js)
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'nonono
Triggersyes infoby using the 'percolation' featureCallbacks are triggered when data changesyes infovia Hawkular Alertingnoyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on CassandraSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornononono
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, allEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.Memcached and Redis integrationnoyesyes
User concepts infoAccess controlyes, based on authentication and database rulesnoRole based access control and fine grained access rightsno
More information provided by the system vendor
ElasticsearchFirebase Realtime DatabaseHawkular MetricsMilvusOracle Berkeley DB
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
ElasticsearchFirebase Realtime DatabaseHawkular MetricsMilvusOracle Berkeley DB
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