DBMS > Bangdb vs. GigaSpaces vs. Sphinx vs. Tkrzw vs. ToroDB

System Properties Comparison Bangdb vs. GigaSpaces vs. Sphinx vs. Tkrzw vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Converged and high performance database for device data, events, time series, document and graph

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

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Search engine

Key-value store

Document store

Secondary database models

Spatial DBMS

Graph DBMS
Search engine

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

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

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

github.com/torodb/server

Technical documentation

docs.bangdb.com

docs.gigaspaces.com/latest/landing.html

sphinxsearch.com/docs

Developer

Sachin Sinha, BangDB

Gigaspaces Technologies

Sphinx Technologies Inc.

Mikio Hirabayashi

8Kdata

Initial release

2012

2000

2001

2020

2016

Current release

BangDB 2.0, October 2021

15.5, September 2020

3.5.1, February 2023

0.9.3, August 2020

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPL version 2, commercial licence available

Open Source

Apache Version 2.0

Open Source

AGPL-V3

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, C++

Java, C++, .Net

C++

Java

Server operating systems

Linux

Linux
macOS
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
macOS

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

string, integer, double, boolean, date, object_id

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

secondary, composite, nested, reverse, geospatial

yes

full-text index on all search fields

SQL

Support of SQL

SQL like support with command line tool

SQL-99 for query and DML statements

SQL-like query language (SphinxQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

Proprietary protocol

Supported programming languages

C
C#
C++
Java
Python

.Net
C++
Java
Python
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

Source-replica replication

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

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

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

using specific database classes

User concepts

Access control

yes (enterprise version only)

Role-based access control

Access rights for users and roles

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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