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DBMS > Brytlyt vs. Databricks vs. Google Cloud Datastore vs. HBase

System Properties Comparison Brytlyt vs. Databricks vs. Google Cloud Datastore vs. HBase

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLThe 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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMSDocument store
Relational DBMS
Document storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Websitebrytlyt.iowww.databricks.comcloud.google.com/­datastorehbase.apache.org
Technical documentationdocs.brytlyt.iodocs.databricks.comcloud.google.com/­datastore/­docshbase.apache.org/­book.html
DeveloperBrytlytDatabricksGoogleApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release2016201320082008
Current release5.0, August 20232.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAJava
Server operating systemsLinux
OS X
Windows
hostedhostedLinux
Unix
Windows infousing Cygwin
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possible
Typing infopredefined data types such as float or dateyesyes, details hereoptions to bring your own types, AVRO
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.yes infospecific XML-type available, but no XML query functionality.yesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyeswith Databricks SQLSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLuser defined functions and aggregatesusing Google App Engineyes infoCoprocessors in Java
TriggersyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
BrytlytDatabricksGoogle Cloud DatastoreHBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BrytlytDatabricksGoogle Cloud DatastoreHBase
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