DBMS > BaseX vs. BigObject vs. Ehcache vs. GridDB vs. STSdb

System Properties Comparison BaseX vs. BigObject vs. Ehcache vs. GridDB vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Analytic DBMS for real-time computations and queries

A widely adopted Java cache with tiered storage options

Scalable in-memory time series database optimized for IoT and Big Data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Native XML DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Time Series DBMS

Key-value store

Secondary database models

Key-value store
Relational DBMS

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

Score	1.73
Rank	#142	Overall
	#4	Native XML DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

docs.basex.org

docs.bigobject.io

www.ehcache.org/documentation

docs.griddb.net

Developer

BaseX GmbH

BigObject, Inc.

Terracotta Inc, owned by Software AG

Toshiba Corporation

STS Soft SC

Initial release

2007

2015

2009

2013

2011

Current release

10.7, August 2023

3.10.0, March 2022

5.1, August 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSD license

commercial

free community edition available

Open Source

Apache Version 2; commercial licenses available

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

GPLv2, commercial license available

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

C++

Server operating systems

Linux
OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

XQuery supports types

yes

numerical, string, blob, geometry, boolean, timestamp

yes

primitive types and user defined types (classes)

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

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

fluentd
ODBC
RESTful HTTP API

JCache

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

.NET Client API

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

Java

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

yes

Lua

Triggers

yes

via events

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by using Terracotta Server

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

none

Tunable Consistency (Strong, Eventual, Weak)

Immediate consistency within container, eventual consistency across containers

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

multiple readers, single writer

yes

supports JTA and can work as an XA resource

ACID at container level

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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