DBMS > Microsoft Azure Table Storage vs. ObjectBox vs. Sphinx vs. ToroDB vs. WakandaDB

System Properties Comparison Microsoft Azure Table Storage vs. ObjectBox vs. Sphinx vs. ToroDB vs. WakandaDB

Editorial information provided by DB-Engines

Name

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

Description

A Wide Column Store for rapid development using massive semi-structured datasets

Extremely fast embedded database for small devices, IoT and Mobile

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

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Time Series DBMS

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

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

azure.microsoft.com/en-us/services/storage/tables

objectbox.io

sphinxsearch.com

github.com/torodb/server

wakanda.github.io

Technical documentation

docs.objectbox.io

sphinxsearch.com/docs

wakanda.github.io/doc

Developer

Microsoft

ObjectBox Limited

Sphinx Technologies Inc.

8Kdata

Wakanda SAS

Initial release

2012

2017

2001

2016

2012

Current release

3.5.1, February 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

GPL version 2, commercial licence available

Open Source

AGPL-V3

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++

Java

C++, JavaScript

Server operating systems

hosted

Android
iOS
Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

All OS with a Java 7 VM

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

Proprietary native API

Proprietary protocol

RESTful HTTP API

Supported programming languages

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

online/offline synchronization between client and server

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

User concepts

Access control

Access rights based on private key authentication or shared access signatures

yes

Access rights for users and roles

yes

More information provided by the system vendor

News

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

Vector Databases for Edge AI
9 August 2023

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

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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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