DBMS > Heroic vs. IBM Cloudant vs. Kingbase vs. mSQL vs. Tarantool

System Properties Comparison Heroic vs. IBM Cloudant vs. Kingbase vs. mSQL vs. Tarantool

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Database as a Service offering based on Apache CouchDB

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

mSQL (Mini SQL) is a simple and lightweight RDBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Time Series DBMS

Document store

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

github.com/spotify/heroic

www.ibm.com/products/cloudant

www.kingbase.com.cn

hughestech.com.au/products/msql

www.tarantool.io

Technical documentation

spotify.github.io/heroic

cloud.ibm.com/docs/Cloudant

www.tarantool.io/en/doc

Developer

Spotify

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

BeiJing KINGBASE Information technologies inc.

Hughes Technologies

Initial release

2014

2010

1999

1994

2008

Current release

V8.0, August 2021

4.4, October 2021

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

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

Java

Erlang

C and Java

C and C++

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

BSD
Linux
macOS

Data scheme

schema-free

yes

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

via Elasticsearch

yes

SQL

Support of SQL

Standard with numerous extensions

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

Full-featured ANSI SQL support

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

RESTful HTTP/JSON API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

JDBC
ODBC

Open binary protocol

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

Lua, C and SQL stored procedures

Triggers

yes

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

none

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

none

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

In-memory capabilities

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

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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