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DBMS > Faircom DB vs. HBase vs. HyperSQL vs. PouchDB vs. Vertica

System Properties Comparison Faircom DB vs. HBase vs. HyperSQL vs. PouchDB vs. Vertica

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonHBase  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonPouchDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Wide-column store based on Apache Hadoop and on concepts of BigTableMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBJavaScript 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 modelKey-value store
Relational DBMS
Wide column storeRelational DBMSDocument storeRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbhbase.apache.orghsqldb.orgpouchdb.comwww.vertica.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhbase.apache.org/­book.htmlhsqldb.org/­web/­hsqlDocsFrame.htmlpouchdb.com/­guidesvertica.com/­documentation
DeveloperFairCom CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software FoundationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release19792008200120122005
Current releaseV12, November 20202.3.4, January 20212.7.2, June 20237.1.1, June 201912.0.3, January 2023
License infoCommercial or Open Sourcecommercial infoRestricted, free version availableOpen Source infoApache version 2Open Source infobased on BSD licenseOpen Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono 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 languageANSI C, C++JavaJavaJavaScriptC++
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Unix
Windows infousing Cygwin
All OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesserver-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeschema free, schema optional, schema required, partial schema,schema-free, schema definition possibleyesschema-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 dateyes, ANSI SQL Types, JSON, typed binary structuresoptions to bring your own types, AVROyesnoyes
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 indexesyesnoyesyes infovia viewsNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsnoyesnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RESTful HTTP API
Thrift
HTTP API infoJDBC via HTTP
JDBC
ODBC
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
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC
Java
JavaScriptC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infoCoprocessors in JavaJava, SQLView functions in JavaScriptyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesyesyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingnoneSharding infowith a proxy-based framework, named couchdb-loungehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication
Source-replica replication
noneMulti-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 methodsnoyesnoyesno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentSingle row ACID (across millions of columns)ACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes 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.yesyesyesyesno
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Faircom DB infoformerly c-treeACEHBaseHyperSQL infoalso known as HSQLDBPouchDBVertica 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
Faircom DB infoformerly c-treeACEHBaseHyperSQL infoalso known as HSQLDBPouchDBVertica infoOpenText™ Vertica™
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