DBMS > Amazon DynamoDB vs. Google Cloud Spanner vs. JanusGraph vs. Lovefield vs. Yaacomo

System Properties Comparison Amazon DynamoDB vs. Google Cloud Spanner vs. JanusGraph vs. Lovefield vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Embeddable relational database for web apps written in pure JavaScript

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Relational DBMS

Graph DBMS

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	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

aws.amazon.com/dynamodb

cloud.google.com/spanner

janusgraph.org

google.github.io/lovefield

yaacomo.com

Technical documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/spanner/docs

docs.janusgraph.org

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

Developer

Amazon

Google

Linux Foundation; originally developed as Titan by Aurelius

Google

Q2WEB GmbH

Initial release

2012

2017

2014

2009

Current release

0.6.3, February 2023

2.1.12, February 2017

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Server operating systems

hosted

Linux
OS X
Unix
Windows

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

tested with Chrome, Firefox, IE, Safari

Android
Linux
Windows

Data scheme

schema-free

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

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

Clojure
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

yes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

using Google Cloud Dataflow

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Relationships in graphs

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

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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