DBMS > BigchainDB vs. NSDb vs. SAP IQ vs. Spark SQL vs. Transbase

System Properties Comparison BigchainDB vs. NSDb vs. SAP IQ vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Columnar RDBMS optimized for Big Data analytics

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

column-oriented

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.bigchaindb.com

nsdb.io

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

nsdb.io/Architecture

help.sap.com/docs/SAP_IQ

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

SAP, formerly Sybase

Apache Software Foundation

Transaction Software GmbH

Initial release

2016

2017

1994

2014

1987

Current release

16.1 SPS04, April 2019

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

commercial

free development license

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.

Implementation language

Python

Java, Scala

Scala

C and C++

Server operating systems

Linux

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

CLI Client
RESTful HTTP API

gRPC
HTTP REST
WebSocket

ADO.NET
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Java
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

SAP/Sybase Replication Server

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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

Recent citations in the news

Exploring the 10 BEST Python Libraries for Blockchain Applications
9 September 2023, DataDrivenInvestor

An Introduction to BigchainDB, a Popular Blockchain Database
17 September 2020, Open Source For You

Blockchain Database Startup BigchainDB Raises €3 Million
27 September 2016, CoinDesk

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

What is BigchainDB Technology & How it works and the Characteristics?
26 August 2017, Blockchain Council

provided by Google News

New Services in SAP HANA Cloud Lower TCO for Customers in Data-Intensive, Highly Regulated Industries
7 April 2021, SAP News

SAP Again Named a Leader in 2021 Gartner® Magic Quadrant™ for Cloud Database Management Systems
16 December 2021, SAP News

Independent Research Firm Names SAP a Leader in Data Management for Analytics
17 February 2020, SAP News

SAP Scales Out HANA In-Memory For Clouds
6 March 2014, EnterpriseAI

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

Share this page