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DBMS > GigaSpaces vs. PouchDB vs. Vertica

System Properties Comparison GigaSpaces vs. PouchDB vs. Vertica

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonPouchDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsJavaScript DBMS with an API inspired by CouchDBCloud 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 store
Object oriented DBMS infoValues are user defined objects
Document storeRelational DBMS infoColumn oriented
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.gigaspaces.compouchdb.comwww.vertica.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlpouchdb.com/­guidesvertica.com/­documentation
DeveloperGigaspaces TechnologiesApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release200020122005
Current release15.5, September 20207.1.1, June 201912.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Sourcecommercial 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 languageJava, C++, .NetJavaScriptC++
Server operating systemsLinux
macOS
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)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 dateyesnoyes
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.no infoXML can be used for describing objects metadatanono
Secondary indexesyesyes infovia viewsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-99 for query and DML statementsnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP 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 languages.Net
C++
Java
Python
Scala
JavaScriptC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesView functions in JavaScriptyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes, event driven architectureyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
Multi-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 methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlRole-based access controlnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
GigaSpacesPouchDBVertica 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
GigaSpacesPouchDBVertica infoOpenText™ Vertica™
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