DBMS > BigObject vs. EsgynDB vs. Graph Engine vs. OrigoDB vs. VoltDB

System Properties Comparison BigObject vs. EsgynDB vs. Graph Engine vs. OrigoDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

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

A fully ACID in-memory object graph database

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Graph DBMS
Key-value store

Document store
Object oriented DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

Technical documentation

docs.bigobject.io

www.graphengine.io/docs/manual

origodb.com/docs

docs.voltdb.com

Developer

BigObject, Inc.

Esgyn

Microsoft

Robert Friberg et al

VoltDB Inc.

Initial release

2015

2010

2009

under the name LiveDB

2010

Current release

11.3, April 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

MIT License

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

.NET and C

Java, C++

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

.NET

Linux
Windows

Linux
OS X

for development

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
F#
Visual Basic

.Net

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

yes

Java

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

depending on model

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

Write ahead log

yes

Snapshots and command logging

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

Role based authorization

Users and roles with access to stored procedures

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

provided by Google News

Unveiling Volt Active Data's game-changing approach to limitless app performance
16 October 2023, YourStory

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

provided by Google News

Share this page