DBMS > Blueflood vs. CrateDB vs. Sadas Engine vs. Vertica

System Properties Comparison Blueflood vs. CrateDB vs. Sadas Engine vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Distributed Date Store based on Lucene

SADAS Engine is a columnar DBMS specifically designed for high performance in Data warehouse environments

Cloud or on-premises analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Time Series DBMS

Relational DBMS
Search engine

Relational DBMS

Column oriented

Secondary database models

Document store
Time Series DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.02
Rank	#344	Overall
	#31	Time Series DBMS

Score	0.97
Rank	#178	Overall
	#86	Relational DBMS
	#13	Search engines

Score	0.00
Rank	#354	Overall
	#152	Relational DBMS

Score	19.29
Rank	#38	Overall
	#24	Relational DBMS

Website

Technical documentation

github.com/rackerlabs/blueflood/wiki

crate.io/docs

www.sadasengine.com/index.php/downloads/documentation-columnar-db

vertica.com/documentation

Developer

Rackspace

Crate

SADAS s.r.l.

Micro Focus

prior to that Hewlett Packard

Initial release

2013

2006

2005

Current release

8.0

11.1, February 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

free trial version available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Vertica Accelerator’s high-performance analytics and machine learning with SQL or Python is available as a managed service.

Implementation language

Java

C++

Server operating systems

Linux
OS X

All OS with a Java 7 (and higher) VM

AIX
Linux
Windows

Linux

Data scheme

predefined scheme

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

yes

yes, but unstructured data can be stored in specific Flex-Tables

Typing

predefined data types such as float or date

yes

yes: BINARY, BOOLEAN, CHAR, VARCHAR, LONG VARCHAR, DATE, TIME, TIMESTAMP, INTERVAL, INTERVAL DAY TO SECOND, INTERVAL YEAR TO MONTH, DOUBLE PRECISION, FLOAT, INTEGER, BIGINT, SMALLINT,NUMERIC, DECIMAL, NUMBER, MONEY,GEOMETRY

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.

Secondary indexes

yes

No Indexes Required

SQL

Support of SQL

yes, but no triggers and constraints

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HTTP REST

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

.Net
C
C#
C++
Groovy
Java
PHP
Python

C#
C++
Java
Perl
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

selectable replication factor

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Read Your Own Writes Consistency

for primary key lookups

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

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

managed by 'Learn by Usage'

User concepts

Access control

rights management via user accounts

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

CrateDB is an open source distributed SQL database that spreads data and processing...
» more

Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
» more

Competitive advantages

CrateDB is typically used in operational analytics applications, particularly those...
» more

Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
» more

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
» more

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Market metrics

The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
» more

Licensing and pricing models

CrateDB pricing CrateDB Community Edition is open source and free to use under the...
» more

Cost-based models and subscription-based models are both available. One license is...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

Recent citations in the news

CrateDB 4.5 takes distributed SQL database open source
24 March 2021, TechTarget

Crate.io raises $10M to grow its database platform
15 June 2021, VentureBeat

Crate.io Expands CrateDB Cloud with the Launch of CrateDB Edge
15 April 2021, GlobeNewswire

Crate.io extends database service offering to Google Cloud
13 April 2022, VentureBeat

CrateDB Tackles Machine Analytics with Scale-Out SQL Database
14 December 2016, Datanami

provided by Google News

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15 February 2022, PR Newswire

provided by Google News

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