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DBMS > Bangdb vs. EDB Postgres vs. Google Cloud Bigtable

System Properties Comparison Bangdb vs. EDB Postgres vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSKey-value store
Wide column store
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitebangdb.comwww.enterprisedb.comcloud.google.com/­bigtable
Technical documentationdocs.bangdb.comwww.enterprisedb.com/­docscloud.google.com/­bigtable/­docs
DeveloperSachin Sinha, BangDBEnterpriseDBGoogle
Initial release201220052015
Current releaseBangDB 2.0, October 202114, December 2021
License infoCommercial or Open SourceOpen Source infoBSD 3commercial infoBSD for PostgreSQL-componentscommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++C
Server operating systemsLinuxLinux
Windows
hosted
Data schemeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesno
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.noyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesno
SQL infoSupport of SQLSQL like support with command line toolyes infostandard with numerous extensionsno
APIs and other access methodsProprietary protocol
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC
C#
C++
Java
Python
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyes, Notifications (with Streaming only)yesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmhorizontal partitioning infoby hash, list or rangeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replicationInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyes, multi-version concurrency control (MVCC)yes
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)fine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
BangdbEDB PostgresGoogle Cloud Bigtable
Recent citations in the news

EDB Puts Postgres in the Middle of Analytics Workflow with New Lakehouse Stack
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