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DBMS > Databricks vs. Google Cloud Bigtable vs. Oracle Coherence

System Properties Comparison Databricks vs. Google Cloud Bigtable vs. Oracle Coherence

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Coherence  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.Oracles in-memory data grid solution
Primary database modelDocument store
Relational DBMS
Key-value store
Wide column store
Key-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score60.86
Rank#19  Overall
#3  Document stores
#13  Relational DBMS
Score5.44
Rank#76  Overall
#9  Key-value stores
#7  Wide column stores
Score2.67
Rank#121  Overall
#24  Key-value stores
Websitedatabricks.comcloud.google.com/­bigtablewww.oracle.com/­middleware/­technologies/­coherence.html
Technical documentationdatabricks.com/­documentationcloud.google.com/­bigtable/­docsdocs.oracle.com/­en/­middleware/­standalone/­coherence
DeveloperDatabricksGoogleOracle
Initial release201320152007
Current release12c, September 2016
License infoCommercial or Open SourceOpen Sourcecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemshostedhostedAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
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.yesnono
Secondary indexesyesnono
SQL infoSupport of SQLwith Databricks SQLnono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
RESTful HTTP API
Supported programming languagesPython
R
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C++
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono
Triggersnoyes infoLive Events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesyes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infooptionally
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)authentification to access the cache via certificates or http basic authentication

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More resources
DatabricksGoogle Cloud BigtableOracle Coherence
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