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DBMS > Dragonfly vs. GBase vs. Google Cloud Datastore vs. Ignite

System Properties Comparison Dragonfly vs. GBase vs. Google Cloud Datastore vs. Ignite

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Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonGBase  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonIgnite  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 instanceWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.
Primary database modelKey-value storeRelational DBMSDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.41
Rank#266  Overall
#38  Key-value stores
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.gbase.cncloud.google.com/­datastoreignite.apache.org
Technical documentationwww.dragonflydb.io/­docscloud.google.com/­datastore/­docsapacheignite.readme.io/­docs
DeveloperDragonflyDB team and community contributorsGeneral Data Technology Co., Ltd.GoogleApache Software Foundation
Initial release2023200420082015
Current release1.0, March 2023GBase 8a, GBase 8s, GBase 8cApache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoBSL 1.1commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, Java, PythonC++, Java, .Net
Server operating systemsLinuxLinuxhostedLinux
OS X
Solaris
Windows
Data schemescheme-freeyesschema-freeyes
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysyesyes, details hereyes
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.noyesnoyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoStandard with numerous extensionsSQL-like query language (GQL)ANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
C API
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
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
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresLuauser defined functionsusing Google App Engineyes (compute grid and cache interceptors can be used instead)
Triggerspublish/subscribe channels provide some trigger functionalityyesCallbacks using the Google Apps Engineyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replication using Paxosyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate 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.Immediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.yesnoyes
User concepts infoAccess controlPassword-based authenticationyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementations

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More resources
DragonflyGBaseGoogle Cloud DatastoreIgnite
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