DBMS > Alibaba Cloud Table Store vs. HBase vs. MongoDB vs. RethinkDB vs. Solr

System Properties Comparison Alibaba Cloud Table Store vs. HBase vs. MongoDB vs. RethinkDB vs. Solr

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Wide-column store based on Apache Hadoop and on concepts of BigTable

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Wide column store

Document store

Search engine

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

hbase.apache.org/book.html

www.mongodb.com/docs/manual

rethinkdb.com/docs

solr.apache.org/resources.html

Developer

Alibaba

Apache Software Foundation

Apache top-level project, originally developed by Powerset

MongoDB, Inc

The Linux Foundation

since July 2017

Apache Software Foundation

Initial release

2016

2008

2009

2006

Current release

2.3.4, January 2021

6.0.7, June 2023

2.4.1, August 2020

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Apache Version 2

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java

C++

Java

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

schema-free, schema definition possible

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

yes

string, binary, float, bool, date, geometry

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

Solr Parallel SQL Interface

APIs and other access methods

HTTP API

Java API
RESTful HTTP API
Thrift

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Java API
RESTful HTTP/JSON API

Supported programming languages

Java
Python

C
C#
C++
Groovy
Java
PHP
Python
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

JavaScript

Java plugins

Triggers

yes

in MongoDB Atlas only

Client-side triggers through changefeeds

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-row operations

Single row ACID (across millions of columns)

Multi-document ACID Transactions with snapshot isolation

Atomic single-document operations

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Access rights for users and roles

yes

users and table-level permissions

yes

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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