DBMS > Graphite vs. HEAVY.AI vs. OpenTenBase vs. Stardog

System Properties Comparison Graphite vs. HEAVY.AI vs. OpenTenBase vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

An enterprise-level distributed HTAP open source database based on PostgreSQL

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

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

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.08
Rank	#370	Overall
	#156	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

github.com/graphite-project/graphite-web

github.com/heavyai/heavydb
www.heavy.ai

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

www.stardog.com

Technical documentation

graphite.readthedocs.io

docs.heavy.ai

docs.opentenbase.org
docs.opentenbase.org/en

docs.stardog.com

Developer

Chris Davis

HEAVY.AI, Inc.

OpenAtom Foundation, previously Tencent

Stardog-Union

Initial release

2006

2016

2010

Current release

5.10, January 2022

2.5, January 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD-3

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Python

C++ and CUDA

Java

Server operating systems

Linux
Unix

Linux

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

HTTP API
Sockets

JDBC
ODBC
Thrift
Vega

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

C
Go
Java
PHP
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

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

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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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

show all

Recent citations in the news

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

The value of time series data and TSDBs
10 June 2021, InfoWorld

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

provided by Google News

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