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

System Properties Comparison Blueflood 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

Scalable TimeSeries DBMS based on Cassandra

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

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	0.06
Rank	#353	Overall
	#34	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

blueflood.io

www.gbase.cn

azure.microsoft.com/services/cosmos-db

rocksdb.org

yaacomo.com

Technical documentation

github.com/rax-maas/blueflood/wiki

learn.microsoft.com/azure/cosmos-db

github.com/facebook/rocksdb/wiki

Developer

Rackspace

General Data Technology Co., Ltd.

Microsoft

Facebook, Inc.

Q2WEB GmbH

Initial release

2013

2004

2014

2013

2009

Current release

GBase 8a, GBase 8s, GBase 8c

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

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

Java

C, Java, Python

C++

Server operating systems

Linux
OS X

Linux

hosted

Linux

Android
Linux
Windows

Data scheme

predefined scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

All properties auto-indexed by default

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

yes

APIs and other access methods

HTTP REST

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

.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

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

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

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

yes

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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