DBMS > Blueflood vs. CrateDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. OceanBase

System Properties Comparison Blueflood vs. CrateDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. OceanBase

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Distributed Database based on Lucene

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Globally distributed, horizontally scalable, multi-model database service

A distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Time Series DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

Document store
Wide column store

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.73
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#8	Vector DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

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

Score	1.66
Rank	#147	Overall
	#68	Relational DBMS

Website

blueflood.io

cratedb.com

firebase.google.com/products/realtime-database

azure.microsoft.com/services/cosmos-db

en.oceanbase.com

Technical documentation

github.com/rax-maas/blueflood/wiki

cratedb.com/docs

firebase.google.com/docs/database

learn.microsoft.com/azure/cosmos-db

en.oceanbase.com/docs/oceanbase-database

Developer

Rackspace

Crate

Google

acquired by Google 2014

Microsoft

OceanBase

previously Alibaba and Ant Group

Initial release

2013

2012

2014

2010

Current release

4.3.0, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Open Source

Commercial license available

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.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Implementation language

Java

C++

Server operating systems

Linux
OS X

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux

Data scheme

predefined scheme

Flexible Schema (defined schema, partial schema, schema free)

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

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like query language

yes

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Java
JavaScript
Objective-C

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

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

user defined functions (Javascript)

limited functionality with using 'rules'

JavaScript

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

Callbacks are triggered when data changes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Configurable replication on table/partition-level

yes

Implicit feature of the cloud service

Multi-source replication using Paxos

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

Eventual Consistency
Read-after-write consistency on record level

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

yes

Multi-item ACID transactions with snapshot isolation within a partition

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.

User concepts

Access control

rights management via user accounts

yes, based on authentication and database rules

Access rights can be defined down to the item level

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
» more

OceanBase Database is the world’s only native distributed database that has set new...
» more

Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

High Availability : The five IDCs across three sites disaster recovery solution sets...
» more

Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

OceanBase Database has helped over 400 customers across industries upgrade their...
» more

Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more

TPC-C No.1 Performance , achieved a result of 707.35 million tpmC in the TPC-C benchmark...
» more

Licensing and pricing models

See CrateDB pricing >
» more

Mulan PubL v2 license for open source community edition. Commercial license for enterprise...
» more

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