DBMS > atoti vs. Graph Engine vs. HEAVY.AI vs. Lovefield vs. Newts

System Properties Comparison atoti vs. Graph Engine vs. HEAVY.AI vs. Lovefield vs. Newts

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

Time Series DBMS based on Cassandra

Primary database model

Object oriented DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

atoti.io

www.graphengine.io

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

google.github.io/lovefield

opennms.github.io/newts

Technical documentation

docs.atoti.io

www.graphengine.io/docs/manual

docs.heavy.ai

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

github.com/OpenNMS/newts/wiki

Developer

ActiveViam

Microsoft

HEAVY.AI, Inc.

Google

OpenNMS Group

Initial release

2010

2016

2014

Current release

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

free versions available

Open Source

MIT License

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

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

Java

.NET and C

C++ and CUDA

JavaScript

Java

Server operating systems

.NET

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

yes

schema-free

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

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift
Vega

HTTP REST
Java API

Supported programming languages

C#
C++
F#
Visual Basic

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Java

Server-side scripts

Stored procedures

Python

yes

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

Sharding

Round robin

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

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

yes

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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