DBMS > EsgynDB vs. Graphite vs. Immudb vs. Riak TS

System Properties Comparison EsgynDB vs. Graphite vs. Immudb vs. Riak TS

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Secondary database models

Relational DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.esgyn.cn

github.com/graphite-project/graphite-web

github.com/codenotary/immudb
immudb.io

Technical documentation

graphite.readthedocs.io

docs.immudb.io

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Esgyn

Chris Davis

Codenotary

Open Source, formerly Basho Technologies

Initial release

2015

2006

2020

2015

Current release

1.2.3, April 2022

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

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

C++, Java

Python

Erlang

Server operating systems

Linux

Linux
Unix

BSD
Linux
macOS
Solaris
Windows
z/OS

Linux
OS X

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

restricted

SQL

Support of SQL

yes

SQL-like syntax

yes, limited

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API
Sockets

gRPC protocol
PostgreSQL wire protocol

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

JavaScript (Node.js)
Python

.Net
Go
Java
JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

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.

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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