DBMS > Amazon DynamoDB vs. ObjectBox vs. SQLite vs. Trafodion vs. XTDB

System Properties Comparison Amazon DynamoDB vs. ObjectBox vs. SQLite vs. Trafodion vs. XTDB

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Extremely fast embedded database for small devices, IoT and Mobile

Widely used embeddable, in-process RDBMS

Transactional SQL-on-Hadoop DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Key-value store

Object oriented DBMS

Relational DBMS

Document 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	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

aws.amazon.com/dynamodb

objectbox.io

www.sqlite.org

trafodion.apache.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.objectbox.io

www.sqlite.org/docs.html

trafodion.apache.org/documentation.html

www.xtdb.com/docs

Developer

Amazon

ObjectBox Limited

Dwayne Richard Hipp

Apache Software Foundation, originally developed by HP

Juxt Ltd.

Initial release

2012

2017

2000

2014

2019

Current release

3.46.0 (23 May 2024), May 2024

2.3.0, February 2019

1.19, September 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache License 2.0

Open Source

Public Domain

Open Source

Apache 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++, Java

Clojure

Server operating systems

hosted

Android
iOS
Linux
macOS
Windows

server-less

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

dynamic column types

yes

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

yes

yes, extensible-data-notation format

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

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

All languages supporting JDBC/ODBC/ADO.Net

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

online/offline synchronization between client and server

none

yes, via HBase

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via user defined functions and HBase

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, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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)

yes

fine grained access rights according to SQL-standard

More information provided by the system vendor

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