DBMS > Atos Standard Common Repository vs. BigchainDB vs. FatDB vs. GreptimeDB vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. FatDB vs. GreptimeDB vs. Spark SQL

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

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

Primary database model

Document store
Key-value store

Document store

Document store
Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.bigchaindb.com

greptime.com

spark.apache.org/sql

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.greptime.com

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

Developer

Atos Convergence Creators

FatCloud

Greptime Inc.

Apache Software Foundation

Initial release

2016

2012

2022

2014

Current release

1703

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

Open Source

Apache Version 2.0

Open Source

Apache 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.

Implementation language

Java

Python

Rust

Scala

Server operating systems

Linux

Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

optional

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

Via inetgration in SQL Server

yes

SQL-like DML and DDL statements

APIs and other access methods

LDAP

CLI Client
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

gRPC
HTTP API
JDBC

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

C++
Erlang
Go
Java
JavaScript

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

via applications

Python

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

LDAP bind authentication

yes

Can implement custom security layer via applications

Simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
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Competitive advantages

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Typical application scenarios

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Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
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Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
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Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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