DBMS > Apache Drill vs. DataFS vs. Datastax Enterprise vs. RocksDB

System Properties Comparison Apache Drill vs. DataFS vs. Datastax Enterprise vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store
Relational DBMS

Object oriented DBMS

Wide column store

Key-value store

Secondary database models

Graph DBMS

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

drill.apache.org

newdatabase.com

www.datastax.com/products/datastax-enterprise

rocksdb.org

Technical documentation

drill.apache.org/docs

dev.mobiland.com/Overview.xsp

docs.datastax.com

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Mobiland AG

DataStax

Facebook, Inc.

Initial release

2012

2018

2011

2013

Current release

1.20.3, January 2023

1.1.263, October 2022

6.8, April 2020

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

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

C++

Server operating systems

Linux
OS X
Windows

Windows

Linux
OS X

Linux

Data scheme

schema-free

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

SQL SELECT statement is SQL:2003 compliant

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

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

C++ API
Java API

Supported programming languages

C++

.Net
C
C#
C++
VB.Net

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

no "single point of failure"

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Windows-Profile

Access rights for users can be defined per object

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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