DBMS > Amazon Redshift vs. Apache Phoenix vs. Datastax Enterprise vs. Hive vs. LMDB

System Properties Comparison Amazon Redshift vs. Apache Phoenix vs. Datastax Enterprise vs. Hive vs. LMDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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.

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

A high performant, light-weight, embedded key-value database library

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	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Website

aws.amazon.com/redshift

phoenix.apache.org

www.datastax.com/products/datastax-enterprise

hive.apache.org

www.symas.com/symas-embedded-database-lmdb

Technical documentation

docs.aws.amazon.com/redshift

phoenix.apache.org

docs.datastax.com

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

www.lmdb.tech/doc

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

DataStax

Apache Software Foundation

initially developed by Facebook

Symas

Initial release

2012

2014

2011

2012

2011

Current release

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

6.8, April 2020

3.1.3, April 2022

0.9.32, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2

Open Source

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.

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Implementation language

Java

Server operating systems

hosted

Linux
Unix
Windows

Linux
OS X

All OS with a Java VM

Linux
Unix
Windows

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

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

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JDBC

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

JDBC
ODBC
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

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

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

C++
Java
PHP
Python

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

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

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomicity and isolation are supported for single 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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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 rights for users, groups and roles

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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