DBMS > FeatureBase vs. Google Cloud Bigtable vs. Linter vs. Oracle vs. Vertica

System Properties Comparison FeatureBase vs. Google Cloud Bigtable vs. Linter vs. Oracle vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

RDBMS for high security requirements

Widely used RDBMS

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

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Column oriented

Secondary database models

Spatial 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	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

www.featurebase.com

cloud.google.com/bigtable

linter.ru

www.oracle.com/database

www.vertica.com

Technical documentation

docs.featurebase.com

cloud.google.com/bigtable/docs

docs.oracle.com/en/database

vertica.com/documentation

Developer

Molecula and Pilosa Open Source Contributors

Google

relex.ru

Oracle

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2017

2015

1990

1980

2005

Current release

2022, May 2022

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.

Implementation language

C and C++

C++

Server operating systems

Linux
macOS

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

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

Linux

Data scheme

yes

schema-free

yes

Schemaless in JSON and XML columns

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

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 queries

yes

with proprietary extensions

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

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

character-based, interactive, front-end utility

Supported programming languages

Java
Python

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

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

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

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

PL/SQL

also stored procedures in Java possible

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

Multi-source 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 (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Atomic single-row operations

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» 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.