DBMS > BigchainDB vs. FileMaker vs. Kingbase vs. Microsoft SQL Server vs. Qdrant

System Properties Comparison BigchainDB vs. FileMaker vs. Kingbase vs. Microsoft SQL Server vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Microsofts flagship relational DBMS

A high-performance vector database with neural network or semantic-based matching

Primary database model

Document store

Relational DBMS

Vector DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

www.bigchaindb.com

www.claris.com/filemaker

www.kingbase.com.cn

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

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.claris.com/resources/documentation

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

qdrant.tech/documentation

Developer

Claris

a subsidiary of Apple

BeiJing KINGBASE Information technologies inc.

Microsoft

Qdrant

Initial release

2016

1983

1999

1989

2021

Current release

19.4.1, November 2021

V8.0, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

AGPL v3

commercial

restricted free version is available

Open Source

Apache Version 2.0

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.

SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

Python

C and Java

C++

Rust

Server operating systems

Linux

iOS

client part only
Linux
OS X
Windows

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

A http query request can return the data in XML format

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

via plugins

Standard with numerous extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

Filemaker WebDirect
JDBC
ODBC

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

PHP

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

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

user defined functions

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

horizontal partitioning (by range, list and hash) and vertical partitioning

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication, warm standby

since Version 14

yes

yes, but depending on the SQL-Server Edition

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

simple rights management via user accounts and connection to external directory services

fine grained access rights according to SQL-standard

Key-based authentication

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.