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DBMS > Databricks vs. LevelDB vs. PostGIS vs. Tigris

System Properties Comparison Databricks vs. LevelDB vs. PostGIS vs. Tigris

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonLevelDB  Xexclude from comparisonPostGIS  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesSpatial extension of PostgreSQLA 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 storeSpatial DBMSDocument store
Key-value store
Search engine
Time 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
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score0.02
Rank#369  Overall
#51  Document stores
#55  Key-value stores
#24  Search engines
#38  Time Series DBMS
Websitewww.databricks.comgithub.com/­google/­leveldbpostgis.netwww.tigrisdata.com
Technical documentationdocs.databricks.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdpostgis.net/­documentationwww.tigrisdata.com/­docs
DeveloperDatabricksGoogleTigris Data, Inc.
Initial release2013201120052022
Current release1.23, February 20213.4.2, February 2024
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoGPL v2.0Open Source infoApache Version 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
Server operating systemshostedIllumos
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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.yesnoyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLnoyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesPython
R
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functionsno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesnoneyes infobased on PostgreSQLSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes infobased on PostgreSQLyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
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 writesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyes infobased on PostgreSQLAccess rights for users and roles
More information provided by the system vendor
DatabricksLevelDBPostGISTigris
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksLevelDBPostGISTigris
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