DBMS > Manticore Search vs. Microsoft Azure Table Storage vs. ObjectBox vs. Oracle Rdb vs. Snowflake

System Properties Comparison Manticore Search vs. Microsoft Azure Table Storage vs. ObjectBox vs. Oracle Rdb vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Multi-storage database for search, including full-text search.

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

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Search engine

Wide column store

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Time Series DBMS

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

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

manticoresearch.com

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

github.com/objectbox
objectbox.io

www.oracle.com/database/technologies/related/rdb.html

www.snowflake.com

Technical documentation

manual.manticoresearch.com

docs.objectbox.io

www.oracle.com/database/technologies/related/rdb-doc.html

docs.snowflake.net/manuals/index.html

Developer

Manticore Software

Microsoft

ObjectBox Limited

Oracle, originally developed by Digital Equipment Corporation (DEC)

Snowflake Computing Inc.

Initial release

2017

2012

2017

1984

2014

Current release

6.0, February 2023

4.0 (May 2024)

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

GPL version 2

commercial

Bindings are released under Apache 2.0

Apache License 2.0

commercial

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++

C and C++

Server operating systems

FreeBSD
Linux
macOS
Windows

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

HP Open VMS

hosted

Data scheme

Fixed schema

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

yes, plus "flex" map-like types

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

RESTful HTTP API

Proprietary native API

CLI Client
JDBC
ODBC

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Implicit feature of the cloud service

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication based on Galera library

yes

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

Data sync between devices allowing occasional connected databases to work completely offline

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

optimistic locking

ACID

yes, on a single node

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 Manticore 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

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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