DBMS > Dragonfly vs. GBase vs. Google Cloud Bigtable vs. searchxml

System Properties Comparison Dragonfly vs. GBase vs. Google Cloud Bigtable vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Key-value store

Relational DBMS

Key-value store
Wide column store

Native XML DBMS
Search engine

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.gbase.cn

cloud.google.com/bigtable

www.searchxml.net/category/products

Technical documentation

www.dragonflydb.io/docs

cloud.google.com/bigtable/docs

www.searchxml.net/support/handouts

Developer

DragonflyDB team and community contributors

General Data Technology Co., Ltd.

Google

informationpartners gmbh

Initial release

2023

2004

2015

Current release

1.0, March 2023

GBase 8a, GBase 8s, GBase 8c

1.0

License

Commercial or Open Source

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C, Java, Python

C++

Server operating systems

Linux

hosted

Windows

Data scheme

scheme-free

yes

schema-free

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
C API
JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C
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#
C++
Go
Java
JavaScript (Node.js)
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Lua

user defined functions

yes

on the application server

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic execution of command blocks and scripts

ACID

Atomic single-row operations

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Password-based authentication

yes

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Domain, group and role-based access control at the document level and for application services

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