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DBMS > Databricks vs. LevelDB vs. Quasardb vs. TimescaleDB

System Properties Comparison Databricks vs. LevelDB vs. Quasardb vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLevelDB  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesDistributed, high-performance timeseries databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Key-value storeTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.databricks.comgithub.com/­google/­leveldbquasar.aiwww.timescale.com
Technical documentationdocs.databricks.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddoc.quasar.ai/­masterdocs.timescale.com
DeveloperDatabricksGooglequasardbTimescale
Initial release2013201120092017
Current release1.23, February 20213.14.1, January 20242.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C
Server operating systemshostedIllumos
Linux
OS X
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes infointeger and binarynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesnonoyes
Secondary indexesyesnoyes infowith tagsyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoconsistent hashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replication with selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeno
User concepts infoAccess controlnoCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksLevelDBQuasardbTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksLevelDBQuasardbTimescaleDB
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