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DBMS > Databricks vs. Memcached vs. Tigris

System Properties Comparison Databricks vs. Memcached vs. Tigris

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMemcached  Xexclude from comparisonTigris  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 cachingA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelDocument store
Relational DBMS
Key-value storeDocument store
Key-value store
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score18.08
Rank#32  Overall
#4  Key-value stores
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websitewww.databricks.comwww.memcached.orgwww.tigrisdata.com
Technical documentationdocs.databricks.comgithub.com/­memcached/­memcached/­wikiwww.tigrisdata.com/­docs
DeveloperDatabricksDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalTigris Data, Inc.
Initial release201320032022
Current release1.6.27, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoBSD licenseOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedFreeBSD
Linux
OS X
Unix
Windows
Linux
macOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
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 indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocolCLI Client
gRPC
RESTful HTTP API
Supported programming languagesPython
R
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoRepcached, a Memcached patch, provides this functionallityyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno
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, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlyes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights for users and roles
More information provided by the system vendor
DatabricksMemcachedTigris
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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