DBMS > Datastax Enterprise vs. Google BigQuery vs. Oracle vs. UniData,UniVerse vs. Vertica

System Properties Comparison Datastax Enterprise vs. Google BigQuery vs. Oracle vs. UniData,UniVerse vs. Vertica

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS

MultiValue database and application server with SQL mapping layer and meta database capabilities

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

Column oriented

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Spatial DBMS
Time Series DBMS

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

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

www.datastax.com/products/datastax-enterprise

cloud.google.com/bigquery

www.oracle.com/database

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

www.vertica.com

Technical documentation

docs.datastax.com

cloud.google.com/bigquery/docs

docs.oracle.com/en/database

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

vertica.com/documentation

Developer

DataStax

Google

Oracle

Rocket Software

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2011

2010

1980

1985

2005

Current release

6.8, April 2020

23c, September 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

restricted free version is available

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.

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 and C++

C++

Server operating systems

Linux
OS X

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

AIX
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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

optional

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

Secondary indexes

yes

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

SQL

Support of SQL

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

yes

with proprietary extensions

yes

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

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

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

character-based, interactive, front-end utility

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Basic

U2 Basic
C
Java

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL

also stored procedures in Java possible

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

U2 Basic

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding, horizontal partitioning

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

Source-replica replication

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

yes

can be realized in PL/SQL

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

Since BigQuery is designed for querying data

ACID

isolation level can be parameterized

ACID

configurable

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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)

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

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

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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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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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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Cost-based models and subscription-based models are both available. One license is...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.