DBMS > FeatureBase vs. Google BigQuery vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. VelocityDB

System Properties Comparison FeatureBase vs. Google BigQuery vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. VelocityDB

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.

Large scale data warehouse service with append-only tables

Cloud-based data warehousing service

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

Graph DBMS
Object oriented DBMS

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

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS
	#21	Object oriented DBMS

Website

www.featurebase.com

cloud.google.com/bigquery

www.ibm.com/products/db2/warehouse

www.sap.com/products/technology-platform/sql-anywhere.html

velocitydb.com

Technical documentation

docs.featurebase.com

cloud.google.com/bigquery/docs

help.sap.com/docs/SAP_SQL_Anywhere

velocitydb.com/UserGuide

Developer

Molecula and Pilosa Open Source Contributors

Google

IBM

SAP

formerly Sybase

VelocityDB Inc

Initial release

2017

2010

2014

1992

2011

Current release

2022, May 2022

17, July 2015

7.x

License

Commercial or Open Source

commercial

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.

Implementation language

Server operating systems

Linux
macOS

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Any that supports .NET

Data scheme

yes

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL queries

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
HTTP API
JDBC
ODBC

.Net

Supported programming languages

Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

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

.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL, SQL PL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

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

User concepts

Access control

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

Based on Windows Authentication

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