DBMS > BigchainDB vs. GeoSpock vs. Google Cloud Bigtable vs. Graphite vs. Microsoft SQL Server

System Properties Comparison BigchainDB vs. GeoSpock vs. Google Cloud Bigtable vs. Graphite vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Microsofts flagship relational DBMS

Primary database model

Document store

Relational DBMS

Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

www.bigchaindb.com

geospock.com

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

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

Technical documentation

bigchaindb.readthedocs.io/en/latest

cloud.google.com/bigtable/docs

graphite.readthedocs.io

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

Developer

GeoSpock

Google

Chris Davis

Microsoft

Initial release

2016

2015

2006

1989

Current release

2.0, September 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

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, Javascript

Python

C++

Server operating systems

Linux

hosted

Linux
Unix

Linux
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
Sockets

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

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

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

Automatic sharding

Sharding

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

Internal replication in Colossus, and regional replication between two clusters in different zones

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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 can be defined per table

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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