DBMS > Amazon Redshift vs. Blueflood vs. GreptimeDB vs. JanusGraph

System Properties Comparison Amazon Redshift vs. Blueflood vs. GreptimeDB vs. JanusGraph

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on Cassandra

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Website

aws.amazon.com/redshift

blueflood.io

greptime.com

janusgraph.org

Technical documentation

docs.aws.amazon.com/redshift

github.com/rax-maas/blueflood/wiki

docs.greptime.com

docs.janusgraph.org

Developer

Amazon (based on PostgreSQL)

Rackspace

Greptime Inc.

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2012

2013

2022

2017

Current release

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Java

Rust

Java

Server operating systems

hosted

Linux
OS X

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

predefined scheme

schema-free, schema definition possible

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

HTTP REST

gRPC
HTTP API
JDBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

All languages supporting JDBC/ODBC

C++
Erlang
Go
Java
JavaScript

Clojure
Java
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Simple rights management via user accounts

User authentification and security via Rexster Graph Server

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

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

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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.