DBMS > Amazon DocumentDB vs. Cassandra vs. etcd vs. Google Cloud Bigtable vs. Vertica

System Properties Comparison Amazon DocumentDB vs. Cassandra vs. etcd vs. Google Cloud Bigtable vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A distributed reliable key-value store

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Cloud or off-cloud 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

Wide column store

Key-value store

Key-value store
Wide column store

Relational DBMS

Column oriented

Secondary database models

Vector DBMS

starting with release V5

Spatial DBMS
Time Series DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

aws.amazon.com/documentdb

cassandra.apache.org

etcd.io
github.com/etcd-io/etcd

cloud.google.com/bigtable

www.vertica.com

Technical documentation

aws.amazon.com/documentdb/resources

cassandra.apache.org/doc/latest

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

cloud.google.com/bigtable/docs

vertica.com/documentation

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2019

2008

2015

2005

Current release

4.1.3, July 2023

3.4, August 2019

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Server operating systems

hosted

BSD
Linux
OS X
Windows

FreeBSD
Linux
Windows

experimental

hosted

Linux

Data scheme

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

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

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

gRPC
JSON over HTTP

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

character-based, interactive, front-end utility

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
C++
Go
Java
JavaScript (Node.js)
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, watching key changes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

Representation of geographical distribution of servers is possible

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Internal replication in Colossus, and regional replication between two clusters in different zones

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

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

Atomicity and isolation are supported for single operations

Atomic single-row operations

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

Access rights for users and roles

Access rights for users can be defined per object

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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Cost-based models and subscription-based models are both available. One license is...
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