DBMS > Amazon DynamoDB vs. Apache Druid vs. GeoMesa vs. SpatiaLite vs. Teradata Aster

System Properties Comparison Amazon DynamoDB vs. Apache Druid vs. GeoMesa vs. SpatiaLite vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Spatial extension of SQLite

Platform for big data analytics on multistructured data sources and types

Primary database model

Document store
Key-value store

Relational DBMS
Time Series DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

aws.amazon.com/dynamodb

druid.apache.org

www.geomesa.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.aws.amazon.com/dynamodb

druid.apache.org/docs/latest/design

www.geomesa.org/documentation/stable/user/index.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Amazon

Apache Software Foundation and contributors

CCRi and others

Alessandro Furieri

Teradata

Initial release

2012

2014

2008

2005

Current release

29.0.1, April 2024

5.0.0, May 2024

5.0.0, August 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache license v2

Open Source

Apache License 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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

Java

Scala

C++

Server operating systems

hosted

Linux
OS X
Unix

server-less

Linux

Data scheme

schema-free

yes

schema-less columns are supported

yes

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

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

RESTful HTTP API

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

R packages

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

depending on storage layer

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

depending on storage layer

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

depending on storage layer

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

depending on storage layer

yes

User concepts

Access control

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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