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DBMS > Databricks vs. Google Cloud Bigtable vs. TimescaleDB vs. Warp 10

System Properties Comparison Databricks vs. Google Cloud Bigtable vs. TimescaleDB vs. Warp 10

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTimescaleDB  Xexclude from comparisonWarp 10  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Relational DBMS
Key-value store
Wide column store
Time 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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.databricks.comcloud.google.com/­bigtablewww.timescale.comwww.warp10.io
Technical documentationdocs.databricks.comcloud.google.com/­bigtable/­docsdocs.timescale.comwww.warp10.io/­content/­02_Getting_started
DeveloperDatabricksGoogleTimescaleSenX
Initial release2013201520172015
Current release2.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemshostedhostedLinux
OS X
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or datenonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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 indexesyesnoyesno
SQL infoSupport of SQLwith Databricks SQLnoyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Jupyter
WebSocket
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infoWarpScript
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, across time and space (hash partitioning) attributesSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with hot standby and reads on replicas infoselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
DatabricksGoogle Cloud BigtableTimescaleDBWarp 10
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGoogle Cloud BigtableTimescaleDBWarp 10
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