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DBMS > Cachelot.io vs. TypeDB vs. Vertica

System Properties Comparison Cachelot.io vs. TypeDB vs. Vertica

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Editorial information provided by DB-Engines
NameCachelot.io  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparisonVertica infoVertica Analytics Platform  Xexclude from comparison
DescriptionIn-memory caching systemTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query languageCloud or on-premises 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 storeGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
Relational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.00
Rank#377  Overall
#59  Key-value stores
Score1.27
Rank#174  Overall
#15  Graph DBMS
#85  Relational DBMS
Score18.51
Rank#38  Overall
#23  Relational DBMS
Websitecachelot.iovaticle.comwww.vertica.com
Technical documentationdocs.vaticle.comvertica.com/­documentation
DeveloperVaticle (formerly Grakn Labs)Micro Focus infoprior to that Hewlett Packard
Initial release201520162005
Current release2.14.1, November 202211.1, February 2022
License infoCommercial or Open SourceOpen Source infoSimplified BSD LicenseOpen Source infoGPL Version 3, commercial licenses availablecommercial 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

Providers of DBaaS offerings, please contact us to be listed.
Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.
Implementation languageC++JavaC++
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyes, but unstructured data can be stored in specific Flex-Tables
Typing infopredefined data types such as float or datenoyesyes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY
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 indexesnoyesNo Indexes Required
SQL infoSupport of SQLnonoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsMemcached protocolgRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnonoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoby using Cassandrahorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication infoby using CassandraMulti-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 methodsnoyes infoby using Apache Kafka and Apache Zookeeperno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infosubstituted by the relationship featureyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnoyes infoat REST API level; other APIs in progressfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Cachelot.ioTypeDB infoformerly named GraknVertica infoVertica Analytics Platform
Specific characteristicsMeet TypeDB (and TypeQL ) TypeDB is a strongly-typed database with a rich and logical...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more
Competitive advantagesEntity-Relationship Model TypeDB allows you to model your domain using the well-known...
» more
Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Communication 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 modelsAGPL and Commercial . The commercial license is priced based on cluster resources...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
Cachelot.ioTypeDB infoformerly named GraknVertica infoVertica Analytics Platform
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