DBMS > BigchainDB vs. CrateDB vs. Microsoft Access vs. Snowflake

System Properties Comparison BigchainDB vs. CrateDB vs. Microsoft Access vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

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

Distributed Database based on Lucene

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

www.bigchaindb.com

cratedb.com

www.microsoft.com/en-us/microsoft-365/access

www.snowflake.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

cratedb.com/docs

developer.microsoft.com/en-us/access

docs.snowflake.net/manuals/index.html

Developer

Crate

Microsoft

Snowflake Computing Inc.

Initial release

2016

2013

1992

2014

Current release

5.8.1, August 2024

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

commercial

Bundled with Microsoft Office

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

Python

Java

C++

Server operating systems

Linux

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

but not compliant to any SQL standard

yes

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

since Access 2010 using the ACE-engine

user defined functions

Triggers

yes

since Access 2010 using the ACE-engine

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Configurable replication on table/partition-level

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

but no files for transaction logging

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

rights management via user accounts

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept, user roles and pluggable authentication

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