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DBMS > Badger vs. PouchDB vs. Rockset vs. Vertica

System Properties Comparison Badger vs. PouchDB vs. Rockset vs. Vertica

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonPouchDB  Xexclude from comparisonRockset  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.JavaScript DBMS with an API inspired by CouchDBA scalable, reliable search and analytics service in the cloud, built on RocksDBCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelKey-value storeDocument storeDocument storeRelational DBMS infoColumn oriented
Secondary database modelsRelational DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score2.28
Rank#115  Overall
#21  Document stores
Score0.79
Rank#211  Overall
#35  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitegithub.com/­dgraph-io/­badgerpouchdb.comrockset.comwww.vertica.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerpouchdb.com/­guidesdocs.rockset.comvertica.com/­documentation
DeveloperDGraph LabsApache Software FoundationRocksetOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2017201220192005
Current release7.1.1, June 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Sourcecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesno infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaScriptC++C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)hostedLinux
Data schemeschema-freeschema-freeschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or datenonodynamic typingyes
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.nonono infoingestion from XML files supportedno
Secondary indexesnoyes infovia viewsall fields are automatically indexedNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoRead-only SQL queries, including JOINsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP REST infoonly for PouchDB Server
JavaScript API
HTTP RESTADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGoJavaScriptGo
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoView functions in JavaScriptnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infowith a proxy-based framework, named couchdb-loungeAutomatic shardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlnonoAccess rights for users and organizations can be defined via Rockset consolefine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
BadgerPouchDBRocksetVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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More resources
BadgerPouchDBRocksetVertica infoOpenText™ Vertica™
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