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DBMS > Bangdb vs. Google Cloud Datastore vs. Ingres vs. Teradata

System Properties Comparison Bangdb vs. Google Cloud Datastore vs. Ingres vs. Teradata

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMSA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Graph DBMS
Spatial DBMS
Time Series 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
Score4.47
Rank#76  Overall
#12  Document stores
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitebangdb.comcloud.google.com/­datastorewww.actian.com/­databases/­ingreswww.teradata.com
Technical documentationdocs.bangdb.comcloud.google.com/­datastore/­docsdocs.actian.com/­ingresdocs.teradata.com
DeveloperSachin Sinha, BangDBGoogleActian CorporationTeradata
Initial release201220081974 infooriginally developed at University Berkely in early 1970s1984
Current releaseBangDB 2.0, October 202111.2, May 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C
Server operating systemsLinuxhostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes, details hereyesyes
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.nonono infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL like support with command line toolSQL-like query language (GQL)yesyes infoSQL 2016 + extensions
APIs and other access methodsProprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyesyes infoUDFs, stored procedures, table functions in parallel
Triggersyes, Notifications (with Streaming only)Callbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication using PaxosIngres ReplicatorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes infoMVCCyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes
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 modenonoyes
User concepts infoAccess controlyes (enterprise version only)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
BangdbGoogle Cloud DatastoreIngresTeradata
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