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DBMS > Bangdb vs. Drizzle vs. Google Cloud Datastore vs. RavenDB

System Properties Comparison Bangdb vs. Drizzle vs. Google Cloud Datastore vs. RavenDB

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRavenDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionConverged and high performance database for device data, events, time series, document and graphMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSDocument storeDocument store
Secondary database modelsSpatial DBMSGraph 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
Score2.92
Rank#101  Overall
#18  Document stores
Websitebangdb.comcloud.google.com/­datastoreravendb.net
Technical documentationdocs.bangdb.comcloud.google.com/­datastore/­docsravendb.net/­docs
DeveloperSachin Sinha, BangDBDrizzle project, originally started by Brian AkerGoogleHibernating Rhinos
Initial release2012200820082010
Current releaseBangDB 2.0, October 20217.2.4, September 20125.4, July 2022
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoGNU GPLcommercialOpen Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++C#
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedLinux
macOS
Raspberry Pi
Windows
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyes, details hereno
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.nono
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyesyes
SQL infoSupport of SQLSQL like support with command line toolyes infowith proprietary extensionsSQL-like query language (GQL)SQL-like query language (RQL)
APIs and other access methodsProprietary protocol
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC
C#
C++
Java
Python
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnonousing Google App Engineyes
Triggersyes, Notifications (with Streaming only)no infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyes
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
Source-replica replication
Multi-source replication using PaxosMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowyes
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.Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID, Cluster-wide transaction available
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 modeno
User concepts infoAccess controlyes (enterprise version only)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Authorization levels configured per client per database

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More resources
BangdbDrizzleGoogle Cloud DatastoreRavenDB
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