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DBMS > Databricks vs. Memcached vs. Vertica

System Properties Comparison Databricks vs. Memcached vs. Vertica

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMemcached  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.In-memory key-value store, originally intended for cachingCloud 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
Relational DBMS
Key-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
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score16.84
Rank#32  Overall
#4  Key-value stores
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitewww.databricks.comwww.memcached.orgwww.vertica.com
Technical documentationdocs.databricks.comgithub.com/­memcached/­memcached/­wikivertica.com/­documentation
DeveloperDatabricksDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalOpenText infopreviously Micro Focus and Hewlett Packard
Initial release201320032005
Current release1.6.29, June 202412.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnono 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 languageCC++
Server operating systemshostedFreeBSD
Linux
OS X
Unix
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-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 datenoyes
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.yesno
Secondary indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLwith Databricks SQLnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocolADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesPython
R
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoRepcached, a Memcached patch, provides this functionallityMulti-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 methodsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlyes infousing SASL (Simple Authentication and Security Layer) protocolfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
DatabricksMemcachedVertica infoOpenText™ Vertica™
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksMemcachedVertica infoOpenText™ Vertica™
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