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DBMS > Bangdb vs. Google Cloud Datastore vs. Greenplum vs. Milvus

System Properties Comparison Bangdb vs. Google Cloud Datastore vs. Greenplum vs. Milvus

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonMilvus  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 PlatformAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Document storeRelational DBMSVector DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial 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
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score2.78
Rank#103  Overall
#3  Vector DBMS
Websitebangdb.comcloud.google.com/­datastoregreenplum.orgmilvus.io
Technical documentationdocs.bangdb.comcloud.google.com/­datastore/­docsdocs.greenplum.orgmilvus.io/­docs/­overview.md
DeveloperSachin Sinha, BangDBGooglePivotal Software Inc.
Initial release2012200820052019
Current releaseBangDB 2.0, October 20217.0.0, September 20232.3.4, January 2024
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen Source infoApache 2.0Open Source infoApache Version 2.0
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.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC, C++C++, Go
Server operating systemsLinuxhostedLinuxLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes, details hereyesVector, Numeric and String
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.nonoyes infosince Version 4.2no
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesno
SQL infoSupport of SQLSQL like support with command line toolSQL-like query language (GQL)yesno
APIs and other access methodsProprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnousing Google App Engineyesno
Triggersyes, Notifications (with Streaming only)Callbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication using PaxosSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
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 ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
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-standardRole based access control and fine grained access rights
More information provided by the system vendor
BangdbGoogle Cloud DatastoreGreenplumMilvus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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BangdbGoogle Cloud DatastoreGreenplumMilvus
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