DBMS > Altibase vs. Amazon SimpleDB vs. Apache IoTDB vs. Manticore Search vs. Microsoft Azure Cosmos DB

System Properties Comparison Altibase vs. Amazon SimpleDB vs. Apache IoTDB vs. Manticore Search vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

altibase.com

aws.amazon.com/simpledb

iotdb.apache.org

manticoresearch.com

azure.microsoft.com/services/cosmos-db

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.aws.amazon.com/simpledb

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

manual.manticoresearch.com

learn.microsoft.com/azure/cosmos-db

Developer

Altibase

Amazon

Apache Software Foundation

Manticore Software

Microsoft

Initial release

1999

2007

2018

2017

2014

Current release

v7.3, 2023, August 2023

1.1.0, April 2023

6.0, February 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

Apache Version 2.0

Open Source

GPL version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

AIX
HP-UX
Linux

hosted

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

yes

schema-free

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

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

yes

JSON types

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

Secondary indexes

yes

All columns are indexed automatically

yes

full-text index on all search fields

yes

All properties auto-indexed by default

SQL

Support of SQL

ANSI SQL-92

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

JDBC
Native API

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

C
C++
Java

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

C
C#
C++
Go
Java
Python
Scala

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

user defined functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

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

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Synchronous replication based on Galera library

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Strong Consistency with Raft

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

yes

isolated transactions for atomic changes and binary logging for safe writes

Multi-item ACID transactions with snapshot isolation within a partition

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

Access rights can be defined down to the item level

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