DBMS > Bangdb vs. GBase vs. Microsoft Azure Cosmos DB vs. RocksDB vs. Yaacomo

System Properties Comparison Bangdb vs. GBase vs. Microsoft Azure Cosmos DB vs. RocksDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Converged and high performance database for device data, events, time series, document and graph

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

Globally distributed, horizontally scalable, multi-model database service

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

bangdb.com

www.gbase.cn

azure.microsoft.com/services/cosmos-db

rocksdb.org

yaacomo.com

Technical documentation

docs.bangdb.com

learn.microsoft.com/azure/cosmos-db

github.com/facebook/rocksdb/wiki

Developer

Sachin Sinha, BangDB

General Data Technology Co., Ltd.

Microsoft

Facebook, Inc.

Q2WEB GmbH

Initial release

2012

2004

2014

2013

2009

Current release

BangDB 2.0, October 2021

GBase 8a, GBase 8s, GBase 8c

8.11.4, April 2024

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C, Java, Python

C++

Server operating systems

Linux

hosted

Linux

Android
Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

JSON types

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

secondary, composite, nested, reverse, geospatial

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL like support with command line tool

Standard with numerous extensions

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

C++ API
Java API

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

JavaScript

Triggers

yes, Notifications (with Streaming only)

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

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

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Implicit feature of the cloud service

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

yes

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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