DBMS > Amazon DynamoDB vs. Dgraph vs. Google Cloud Spanner vs. Hazelcast vs. Sqrrl

System Properties Comparison Amazon DynamoDB vs. Dgraph vs. Google Cloud Spanner vs. Hazelcast vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

Distributed and scalable native Graph DBMS

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 widely adopted in-memory data grid

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Key-value store

Graph DBMS

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Website

aws.amazon.com/dynamodb

dgraph.io

cloud.google.com/spanner

hazelcast.com

sqrrl.com

Technical documentation

docs.aws.amazon.com/dynamodb

dgraph.io/docs

cloud.google.com/spanner/docs

hazelcast.org/imdg/docs

Developer

Amazon

Dgraph Labs, Inc.

Google

Hazelcast

Amazon

originally Sqrrl Data, Inc.

Initial release

2012

2016

2017

2008

2012

Current release

5.3.6, November 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2; commercial licenses available

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

Server operating systems

hosted

Linux
OS X
Windows

hosted

All OS with a Java VM

Linux

Data scheme

schema-free

yes

schema-free

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

SQL-like query language

APIs and other access methods

RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
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

JCache
JPA
Memcached protocol
RESTful HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

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

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Triggers

yes

by integration with AWS Lambda

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

Multi-source replication with 3 replicas for regional instances.

yes

Replicated Map

selectable replication factor

making use of Hadoop

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

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

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

one or two-phase-commit; repeatable reads; read commited

Atomic updates per row, document, or graph entity

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.

yes

User concepts

Access control

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

Planned for future releases

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

Role-based access control

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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