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DBMS > Dragonfly vs. EsgynDB vs. Google Cloud Bigtable vs. Hazelcast

System Properties Comparison Dragonfly vs. EsgynDB vs. Google Cloud Bigtable vs. Hazelcast

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle'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 grid
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Key-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
Score0.49
Rank#261  Overall
#38  Key-value stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.esgyn.cncloud.google.com/­bigtablehazelcast.com
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docs
DeveloperDragonflyDB team and community contributorsEsgynGoogleHazelcast
Initial release2023201520152008
Current release1.0, March 20235.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialOpen Source infoApache Version 2; commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++, JavaJava
Server operating systemsLinuxLinuxhostedAll OS with a Java VM
Data schemescheme-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesnoyes
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.nononoyes infothe object must implement a serialization strategy
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyesnoSQL-like query language
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresLuaJava Stored Proceduresnoyes infoEvent Listeners, Executor Services
Triggerspublish/subscribe channels provide some trigger functionalitynonoyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDAtomic single-row operationsone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlPassword-based authenticationfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control

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More resources
DragonflyEsgynDBGoogle Cloud BigtableHazelcast
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