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DBMS > EJDB vs. Google Cloud Bigtable vs. Hazelcast vs. KeyDB

System Properties Comparison EJDB vs. Google Cloud Bigtable vs. Hazelcast vs. KeyDB

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Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A widely adopted in-memory data gridAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelDocument storeKey-value store
Wide column store
Key-value storeKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#296  Overall
#44  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Websitegithub.com/­Softmotions/­ejdbcloud.google.com/­bigtablehazelcast.comgithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsdocs.keydb.dev
DeveloperSoftmotionsGoogleHazelcastEQ Alpha Technology Ltd.
Initial release2012201520082019
Current release5.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoGPLv2commercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC++
Server operating systemsserver-lesshostedAll OS with a Java VMLinux
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idnoyespartial 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.noyes infothe object must implement a serialization strategyno
Secondary indexesnonoyesyes infoby using the Redis Search module
SQL infoSupport of SQLnonoSQL-like query languageno
APIs and other access methodsin-process shared librarygRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
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 proceduresnonoyes infoEvent Listeners, Executor ServicesLua
Triggersnonoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated MapMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyes
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.noyesyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlsimple password-based access control and ACL

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More resources
EJDBGoogle Cloud BigtableHazelcastKeyDB
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