DBMS > BigObject vs. Graphite vs. HEAVY.AI vs. Lovefield

System Properties Comparison BigObject vs. Graphite vs. HEAVY.AI vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

bigobject.io

github.com/graphite-project/graphite-web

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

google.github.io/lovefield

Technical documentation

docs.bigobject.io

graphite.readthedocs.io

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

BigObject, Inc.

Chris Davis

HEAVY.AI, Inc.

Google

Initial release

2015

2006

2016

2014

Current release

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

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

Python

C++ and CUDA

JavaScript

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Unix

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

HTTP API
Sockets

JDBC
ODBC
Thrift
Vega

Supported programming languages

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

Lua

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

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

show all

Recent citations in the news

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

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

How Grafana made observability accessible
12 June 2023, InfoWorld

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

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

provided by Google News

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

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

Making the most of geospatial intelligence
14 April 2023, InfoWorld

OmniSci Gets HEAVY New Name and New CEO
1 March 2022, Datanami

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

provided by Google News

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