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DBMS > Bangdb vs. Databricks vs. Google Cloud Datastore

System Properties Comparison Bangdb vs. Databricks vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphThe 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 Platform
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document store
Relational DBMS
Document store
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websitebangdb.comwww.databricks.comcloud.google.com/­datastore
Technical documentationdocs.bangdb.comdocs.databricks.comcloud.google.com/­datastore/­docs
DeveloperSachin Sinha, BangDBDatabricksGoogle
Initial release201220132008
Current releaseBangDB 2.0, October 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++
Server operating systemsLinuxhostedhosted
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes, details here
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.noyesno
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes
SQL infoSupport of SQLSQL like support with command line toolwith Databricks SQLSQL-like query language (GQL)
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
Python
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions and aggregatesusing Google App Engine
Triggersyes, Notifications (with Streaming only)Callbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate 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.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenono
User concepts infoAccess controlyes (enterprise version only)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
BangdbDatabricksGoogle Cloud Datastore
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BangdbDatabricksGoogle Cloud Datastore
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