DBMS > BigchainDB vs. dBASE vs. HEAVY.AI vs. InfinityDB vs. Microsoft SQL Server

System Properties Comparison BigchainDB vs. dBASE vs. HEAVY.AI vs. InfinityDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

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

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A Java embedded Key-Value Store which extends the Java Map interface

Microsofts flagship relational DBMS

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	11.18
Rank	#44	Overall
	#28	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Website

www.bigchaindb.com

www.dbase.com

github.com/heavyai/heavydb
www.heavy.ai

boilerbay.com

www.microsoft.com/en-us/sql-server

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.dbase.com/support/knowledgebase

docs.heavy.ai

boilerbay.com/infinitydb/manual

learn.microsoft.com/en-US/sql/sql-server

Developer

Asthon Tate

HEAVY.AI, Inc.

Boiler Bay Inc.

Microsoft

Initial release

2016

1979

2016

2002

1989

Current release

dBASE 2019, 2019

5.10, January 2022

4.0

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

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

C++ and CUDA

Java

C++

Server operating systems

Linux

DOS

dBase Classic
Windows

dBase Pro

Linux

All OS with a Java VM

Linux
Windows

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

JDBC
ODBC
Thrift
Vega

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

dBase proprietary IDE

All languages supporting JDBC/ODBC/Thrift
Python

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

The IDE can access stored procedures in other database systems.

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

not for dBase internal data, but IDE does support transactions when accessing external DBMS

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

yes

Access rights for users and roles

fine grained access rights according to SQL-standard

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