DBMS > Blueflood vs. GreptimeDB vs. Microsoft SQL Server vs. OpenQM vs. Snowflake

System Properties Comparison Blueflood vs. GreptimeDB vs. Microsoft SQL Server vs. OpenQM vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Microsofts flagship relational DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

blueflood.io

greptime.com

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.snowflake.com

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.greptime.com

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

docs.snowflake.net/manuals/index.html

Developer

Rackspace

Greptime Inc.

Microsoft

Rocket Software, originally Martin Phillips

Snowflake Computing Inc.

Initial release

2013

2022

1989

1993

2014

Current release

SQL Server 2022, November 2022

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

GPLv2, extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

Rust

C++

Server operating systems

Linux
OS X

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

hosted

Data scheme

predefined scheme

schema-free, schema definition possible

yes

with some exceptions

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

APIs and other access methods

HTTP REST

gRPC
HTTP API
JDBC

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

CLI Client
JDBC
ODBC

Supported programming languages

C++
Erlang
Go
Java
JavaScript

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

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Python

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

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate 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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Simple rights management via user accounts

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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

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

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
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Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
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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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