DBMS > Databricks vs. Datastax Enterprise vs. Oracle Berkeley DB vs. Tkrzw

System Properties Comparison Databricks vs. Datastax Enterprise vs. Oracle Berkeley DB vs. Tkrzw

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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.

Widely used in-process key-value store

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Relational DBMS

Wide column store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

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	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.databricks.com

www.datastax.com/products/datastax-enterprise

www.oracle.com/database/technologies/related/berkeleydb.html

dbmx.net/tkrzw

Technical documentation

docs.databricks.com

docs.datastax.com

docs.oracle.com/cd/E17076_05/html/index.html

Developer

Databricks

DataStax

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Mikio Hirabayashi

Initial release

2013

2011

1994

2020

Current release

6.8, April 2020

18.1.40, May 2020

0.9.3, August 2020

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache Version 2.0

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

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

hosted

Linux
OS X

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS

Data scheme

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

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

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

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Supported programming languages

Python
R
Scala

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate 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

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

using specific database classes

User concepts

Access control

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

5. Databricks
14 May 2024, CNBC

This Is the Platform Nancy Pelosi Used to Make Her Private Investment in Databricks
9 May 2024, Yahoo Finance

AI is Driving Record Sales at Multibillion-Dollar Databricks. An IPO Can Wait …
6 March 2024, The Wall Street Journal

Databricks' New Open Source LLM
8 April 2024, Forbes

Top 5 Lessons Learned from Databricks' Journey from $400M to $1.5B+
23 April 2024, saastr.com

provided by Google News

DataStax previews new Hyper Converged Data Platform for enterprise AI
15 May 2024, VentureBeat

DataStax Launches New Hyper-Converged Data Platform Giving Enterprises the Complete Modern Data Center Suite ...
15 May 2024, businesswire.com

DataStax Rolls Out Vector Search for Astra DB to Support Gen AI
19 July 2023, EnterpriseAI

DataStax announces vector search capabilities in its on-prem Apache Cassandra database
8 August 2023, SDTimes.com

DataStax goes vector searching with Astra DB – Blocks and Files
20 July 2023, Blocks & Files

provided by Google News

ACM recognizes far-reaching technical achievements with special awards
26 May 2021, EurekAlert

Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag
5 March 2019, ADT Magazine

The importance of bitcoin nodes and how to start one
9 May 2014, The Merkle News

The stable version of AlmaLinux 9.0 has already been released
26 May 2022, Linux Adictos

provided by Google News

Share this page