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DBMS > BigObject vs. Drizzle vs. Google Cloud Datastore vs. KeyDB

System Properties Comparison BigObject vs. Drizzle vs. Google Cloud Datastore vs. KeyDB

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Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKeyDB  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.
DescriptionAnalytic DBMS for real-time computations and queriesMySQL 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 PlatformAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSDocument storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitebigobject.iocloud.google.com/­datastoregithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationdocs.bigobject.iocloud.google.com/­datastore/­docsdocs.keydb.dev
DeveloperBigObject, Inc.Drizzle project, originally started by Brian AkerGoogleEQ Alpha Technology Ltd.
Initial release2015200820082019
Current release7.2.4, September 2012
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoGNU GPLcommercialOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
FreeBSD
Linux
OS X
hostedLinux
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details herepartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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
Secondary indexesyesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsSQL-like query language (GQL)no
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresLuanousing Google App EngineLua
Triggersnono infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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.Eventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACL

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More resources
BigObjectDrizzleGoogle Cloud DatastoreKeyDB
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