DBMS > Amazon DynamoDB vs. Google Cloud Bigtable vs. HEAVY.AI vs. LokiJS vs. MarkLogic

System Properties Comparison Amazon DynamoDB vs. Google Cloud Bigtable vs. HEAVY.AI vs. LokiJS vs. MarkLogic

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

In-memory JavaScript DBMS

Operational and transactional Enterprise NoSQL database

Primary database model

Document store
Key-value store

Key-value store
Wide column store

Relational DBMS

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Secondary database models

Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Website

aws.amazon.com/dynamodb

cloud.google.com/bigtable

github.com/heavyai/heavydb
www.heavy.ai

github.com/techfort/LokiJS

www.progress.com/marklogic

Technical documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/bigtable/docs

docs.heavy.ai

techfort.github.io/LokiJS

www.progress.com/marklogic/documentation

Developer

Amazon

Google

HEAVY.AI, Inc.

MarkLogic Corp.

Initial release

2012

2015

2016

2014

2001

Current release

5.10, January 2022

11.0, December 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

commercial

restricted free version is 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 CUDA

JavaScript

C++

Server operating systems

hosted

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL92

APIs and other access methods

RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC
Thrift
Vega

JavaScript API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

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

Server-side scripts

Stored procedures

View functions in JavaScript

yes

via XQuery or JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Atomic single-row operations

atomic operations within a single collection possible

ACID

can act as a resource manager in an XA/JTA transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

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

yes

yes, with Range Indexes

User concepts

Access control

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Role-based access control at the document and subdocument levels

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