DBMS > GigaSpaces vs. LokiJS vs. SAP HANA vs. Sphinx

System Properties Comparison GigaSpaces vs. LokiJS vs. SAP HANA vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

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

In-memory JavaScript DBMS

In-memory, column based data store. Available as appliance or cloud service

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Document store

Relational DBMS

Search engine

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.48
Rank	#262	Overall
	#42	Document stores

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

www.gigaspaces.com

github.com/techfort/LokiJS

www.sap.com/products/hana.html

sphinxsearch.com

Technical documentation

docs.gigaspaces.com/latest/landing.html

techfort.github.io/LokiJS

help.sap.com/hana

sphinxsearch.com/docs

Developer

Gigaspaces Technologies

SAP

Sphinx Technologies Inc.

Initial release

2000

2014

2010

2001

Current release

15.5, September 2020

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

JavaScript

C++

Server operating systems

Linux
macOS
Solaris
Windows

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

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

via views

yes

full-text index on all search fields

SQL

Support of SQL

SQL-99 for query and DML statements

yes

SQL-like query language (SphinxQL)

APIs and other access methods

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

JavaScript API

JDBC
ODBC

Proprietary protocol

Supported programming languages

.Net
C++
Java
Python
Scala

JavaScript

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

View functions in JavaScript

SQLScript, R

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

The original contents of fields are not stored in the Sphinx index.

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

yes

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