DBMS > Apache Phoenix vs. Datastax Enterprise vs. Google BigQuery vs. Hive vs. IBM Cloudant

System Properties Comparison Apache Phoenix vs. Datastax Enterprise vs. Google BigQuery vs. Hive vs. IBM Cloudant

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Large scale data warehouse service with append-only tables

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Database as a Service offering based on Apache CouchDB

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Website

phoenix.apache.org

www.datastax.com/products/datastax-enterprise

cloud.google.com/bigquery

hive.apache.org

www.ibm.com/products/cloudant

Technical documentation

phoenix.apache.org

docs.datastax.com

cloud.google.com/bigquery/docs

cwiki.apache.org/confluence/display/Hive/Home

cloud.ibm.com/docs/Cloudant

Developer

Apache Software Foundation

DataStax

Google

Apache Software Foundation

initially developed by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2014

2011

2010

2012

2010

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

6.8, April 2020

3.1.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

Erlang

Server operating systems

Linux
Unix
Windows

Linux
OS X

hosted

All OS with a Java VM

hosted

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

yes

schema-free

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements (CQL); Spark SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

configurable replication factor, datacenter aware, advanced replication for edge computing

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

Since BigQuery is designed for querying data

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Access rights for users can be defined per object

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

Annual subscription
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