DBMS > BigObject vs. GigaSpaces vs. InfinityDB vs. Stardog

System Properties Comparison BigObject vs. GigaSpaces vs. InfinityDB vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Object oriented DBMS

Values are user defined objects

Key-value store

Graph DBMS
RDF store

Secondary database models

Graph DBMS
Search engine

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

docs.bigobject.io

docs.gigaspaces.com/latest/landing.html

boilerbay.com/infinitydb/manual

docs.stardog.com

Developer

BigObject, Inc.

Gigaspaces Technologies

Boiler Bay Inc.

Stardog-Union

Initial release

2015

2000

2002

2010

Current release

15.5, September 2020

4.0

7.3.0, May 2020

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2; Commercial licenses available

commercial

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

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++, .Net

Java

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
macOS
Solaris
Windows

All OS with a Java VM

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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

schema-free and OWL/RDFS-schema support

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.

XML can be used for describing objects metadata

Import/export of XML data possible

Secondary indexes

yes

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

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-99 for query and DML statements

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

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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

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

Supported programming languages

.Net
C++
Java
Python
Scala

Java

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes, event driven architecture

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

yes

relationships in graphs

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

Role-based access control

Access rights for users and roles

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