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DBMS > Bangdb vs. Google Cloud Datastore vs. Graphite vs. TimesTen

System Properties Comparison Bangdb vs. Google Cloud Datastore vs. Graphite vs. TimesTen

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGraphite  Xexclude from comparisonTimesTen  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 PlatformData logging and graphing tool for time series data infoThe storage layer (fixed size database) is called WhisperIn-Memory RDBMS compatible to Oracle
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeTime Series DBMSRelational DBMS
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
Score4.36
Rank#72  Overall
#12  Document stores
Score4.83
Rank#67  Overall
#4  Time Series DBMS
Score1.36
Rank#161  Overall
#75  Relational DBMS
Websitebangdb.comcloud.google.com/­datastoregithub.com/­graphite-project/­graphite-webwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.bangdb.comcloud.google.com/­datastore/­docsgraphite.readthedocs.iodocs.oracle.com/­database/­timesten-18.1
DeveloperSachin Sinha, BangDBGoogleChris DavisOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2012200820061998
Current releaseBangDB 2.0, October 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++Python
Server operating systemsLinuxhostedLinux
Unix
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes, details hereNumeric data onlyyes
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.nononono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesnoyes
SQL infoSupport of SQLSQL like support with command line toolSQL-like query language (GQL)noyes
APIs and other access methodsProprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Sockets
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C#
C++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript (Node.js)
Python
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnousing Google App EnginenoPL/SQL
Triggersyes, Notifications (with Streaming only)Callbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication using PaxosnoneMulti-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.noneImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyes infolockingyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyes infoby means of logfiles and checkpoints
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 modenoyes
User concepts infoAccess controlyes (enterprise version only)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
BangdbGoogle Cloud DatastoreGraphiteTimesTen
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