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DBMS > PouchDB vs. Tkrzw vs. Vertica

System Properties Comparison PouchDB vs. Tkrzw vs. Vertica

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Editorial information provided by DB-Engines
NamePouchDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionJavaScript DBMS with an API inspired by CouchDBA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetCloud 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 modelDocument storeKey-value storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.34
Rank#112  Overall
#21  Document stores
Score0.07
Rank#372  Overall
#57  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitepouchdb.comdbmx.net/­tkrzwwww.vertica.com
Technical documentationpouchdb.com/­guidesvertica.com/­documentation
DeveloperApache Software FoundationMikio HirabayashiOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201220202005
Current release7.1.1, June 20190.9.3, August 202012.0.3, January 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono 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 languageJavaScriptC++C++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux
macOS
Linux
Data schemeschema-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 datenonoyes
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
Secondary indexesyes infovia viewsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsHTTP REST infoonly for PouchDB Server
JavaScript API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesJavaScriptC++
Java
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresView functions in JavaScriptnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infowith a proxy-based framework, named couchdb-loungenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneMulti-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 methodsyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyes 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.yesyes infousing specific database classesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
PouchDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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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...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
PouchDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetVertica infoOpenText™ Vertica™
DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
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