DBMS > Couchbase vs. CrateDB vs. Vertica

System Properties Comparison Couchbase vs. CrateDB vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

A distributed document store with a powerful search engine and in-built operational and analytical capabilities

Distributed Date Store based on Lucene

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

Document store

Relational DBMS
Search engine

Relational DBMS

Column oriented

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension

Document store
Time Series DBMS

Spatial DBMS
Time Series DBMS

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

Score	28.38
Rank	#30	Overall
	#5	Document stores

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

Score	19.29
Rank	#38	Overall
	#24	Relational DBMS

Website

www.couchbase.com

crate.io

www.vertica.com

Technical documentation

docs.couchbase.com

crate.io/docs

vertica.com/documentation

Developer

Couchbase, Inc.

Crate

Micro Focus

prior to that Hewlett Packard

Initial release

2011

2013

2005

Current release

Server: 7.0, July 2021; Mobile: 3, February 2022; Couchbase Capella, October 2021

11.1, February 2022

License

Commercial or Open Source

Open Source

Apache version 2; Commercial licenses also available

Open Source

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.

Couchbase Capella: a fully managed database-as-a-service that eliminates database management efforts and reduces cost

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

Implementation language

C, C++, Go and Erlang

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java 7 (and higher) VM

Linux

Data scheme

schema-free

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

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

Typing

predefined data types such as float or date

yes

String, Boolean, Number

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

Declarative query language (N1QL) that extends ANSI SQL to JSON. First commercial implementation of SQL++.

yes, but no triggers and constraints

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

APIs and other access methods

Native language bindings for CRUD, Query, Search and Analytics APIs

ADO.NET

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

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

character-based, interactive, front-end utility

Supported programming languages

.Net
C
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Scala

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

C#
C++
Java
Perl
PHP
Python
R

Server-side scripts

Stored procedures

Functions and timers in JavaScript

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

via the TAP protocol

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

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

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

ACID

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

Ephemeral buckets

User concepts

Access control

User and Administrator separation with password-based and LDAP integrated Authentication

rights management via user accounts

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

More information provided by the system vendor

Specific characteristics

Developed as an alternative to traditionally inflexible relational databases, Couchbase...
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CrateDB is an open source distributed SQL database that spreads data and processing...
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Deploy-anywhere database for large-scale analytical deployments. Deploy on-premises,...
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Competitive advantages

Couchbase was architected with several differentiated capabilities: Shared-nothing,...
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CrateDB is typically used in operational analytics applications, particularly those...
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Fast, scalable and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Customer 360 for user profile, session store and data aggregation (Comcast, Equifax,...
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CrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Amadeus, AT&T, BD (Becton, Dickinson and Company), Carrefour, Cisco, Comcast, Disney,...
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CrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics

Named a leader in the Forrester Wave™: Big Data NoSQL, Q1 2019 Over 10M downloads...
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The CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
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Licensing and pricing models

The Community Edition (CE) of Couchbase Server and Couchbase Mobile are available...
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CrateDB pricing CrateDB Community Edition is open source and free to use under the...
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Cost-based models and subscription-based models are both available. One license is...
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