DBMS > EsgynDB vs. InfinityDB vs. Snowflake vs. TerminusDB vs. VoltDB

System Properties Comparison EsgynDB vs. InfinityDB vs. Snowflake vs. TerminusDB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

A Java embedded Key-Value Store which extends the Java Map interface

Cloud-based data warehousing service for structured and semi-structured data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Secondary database models

Document store
RDF store

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

boilerbay.com/infinitydb/manual

docs.snowflake.net/manuals/index.html

terminusdb.github.io/terminusdb/#

docs.voltdb.com

Developer

Esgyn

Boiler Bay Inc.

Snowflake Computing Inc.

DataChemist Ltd.

VoltDB Inc.

Initial release

2015

2002

2014

2018

2010

Current release

4.0

11.0.0, January 2023

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

GPL V3

Open Source

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

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

Java

Prolog, Rust

Java, C++

Server operating systems

Linux

All OS with a Java VM

hosted

Linux

Linux
OS X

for development

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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.

yes

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

CLI Client
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java

JavaScript (Node.js)
Python

JavaScript
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

Java

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

yes

Journaling Streams

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

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

in-memory journaling

yes

Snapshots and command logging

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

Users with fine-grained authorization concept, user roles and pluggable authentication

Role-based access control

Users and roles with access to stored procedures

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