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DBMS > Dragonfly vs. EsgynDB vs. Google Cloud Bigtable vs. H2

System Properties Comparison Dragonfly vs. EsgynDB vs. Google Cloud Bigtable vs. H2

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonH2  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.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.esgyn.cncloud.google.com/­bigtablewww.h2database.com
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­bigtable/­docswww.h2database.com/­html/­main.html
DeveloperDragonflyDB team and community contributorsEsgynGoogleThomas Mueller
Initial release2023201520152005
Current release1.0, March 20232.2.220, July 2023
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)
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-freeyes
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.nononono
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyesnoyes
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)
JDBC
ODBC
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
Java
Server-side scripts infoStored proceduresLuaJava Stored ProceduresnoJava Stored Procedures and User-Defined Functions
Triggerspublish/subscribe channels provide some trigger functionalitynonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
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 zonesWith clustering: 2 database servers on different computers operate on identical copies of a database
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
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
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyes, multi-version concurrency control (MVCC)
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)fine grained access rights according to SQL-standard

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More resources
DragonflyEsgynDBGoogle Cloud BigtableH2
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