DBMS > Amazon DynamoDB vs. GeoSpock vs. OrientDB vs. PlanetScale

System Properties Comparison Amazon DynamoDB vs. GeoSpock vs. OrientDB vs. PlanetScale

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

Multi-model DBMS (Document, Graph, Key/Value)

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial 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	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	1.59
Rank	#151	Overall
	#70	Relational DBMS

Website

aws.amazon.com/dynamodb

geospock.com

orientdb.org

planetscale.com

Technical documentation

docs.aws.amazon.com/dynamodb

www.orientdb.com/docs/last/index.html

planetscale.com/docs

Developer

Amazon

GeoSpock

OrientDB LTD; CallidusCloud; SAP

PlanetScale

Initial release

2012

2010

2020

Current release

2.0, September 2019

3.2.29, March 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache version 2

commercial

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, Javascript

Java

Server operating systems

hosted

All OS with a Java JDK (>= JDK 6)

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

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.

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language, no joins

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

JDBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java, Javascript

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationship in graphs

yes

not for MyISAM storage engine

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

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

yes

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 can be defined per table

Access rights for users and roles; record level security configurable

Users with fine-grained authorization concept

no user groups or roles

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