DBMS > EsgynDB vs. Lovefield vs. Speedb vs. Stardog vs. VoltDB

System Properties Comparison EsgynDB vs. Lovefield vs. Speedb vs. Stardog vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

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

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

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.26
Rank	#310	Overall
	#45	Key-value stores

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

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.esgyn.cn

google.github.io/lovefield

www.speedb.io

www.stardog.com

www.voltdb.com

Technical documentation

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

docs.stardog.com

docs.voltdb.com

Developer

Esgyn

Google

Speedb

Stardog-Union

VoltDB Inc.

Initial release

2015

2014

2020

2010

Current release

2.1.12, February 2017

7.3.0, May 2020

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0; commercial license available

commercial

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

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

JavaScript

C++

Java

Java, C++

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Linux
macOS
Windows

Linux
OS X

for development

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

yes

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

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

yes

only a subset of SQL 99

APIs and other access methods

ADO.NET
JDBC
ODBC

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

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions and aggregates, HTTP Server extensions in Java

Java

Triggers

Using read-only observers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

yes

Multi-source replication in HA-Cluster

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes

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

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

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

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more

Competitive advantages

Speedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more

Licensing and pricing models

Open source - Speedb OSS is released under an Apache license and can be found on...
» more

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