DBMS > Amazon DynamoDB vs. GeoSpock vs. Lovefield vs. SQLite vs. TerarkDB

System Properties Comparison Amazon DynamoDB vs. GeoSpock vs. Lovefield vs. SQLite vs. TerarkDB

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

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

Secondary database models

Time Series 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	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

aws.amazon.com/dynamodb

geospock.com

google.github.io/lovefield

www.sqlite.org

github.com/bytedance/terarkdb

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/google/lovefield/blob/master/docs/spec_index.md

www.sqlite.org/docs.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Amazon

GeoSpock

Google

Dwayne Richard Hipp

ByteDance, originally Terark

Initial release

2012

2014

2000

2016

Current release

2.0, September 2019

2.1.12, February 2017

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

Open Source

Public Domain

commercial

restricted open source version 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

Java, Javascript

JavaScript

C++

Server operating systems

hosted

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

tested with Chrome, Firefox, IE, Safari

server-less

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

JDBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

C++ API
Java API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++
Java

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

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

via file-system locks

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

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

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