DBMS > Amazon DynamoDB vs. AnzoGraph DB vs. Badger vs. Ignite vs. Sadas Engine

System Properties Comparison Amazon DynamoDB vs. AnzoGraph DB vs. Badger vs. Ignite vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Key-value store

Graph DBMS
RDF store

Key-value store

Key-value store
Relational 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	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

aws.amazon.com/dynamodb

cambridgesemantics.com/anzograph

github.com/dgraph-io/badger

ignite.apache.org

www.sadasengine.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

godoc.org/github.com/dgraph-io/badger

apacheignite.readme.io/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Amazon

Cambridge Semantics

DGraph Labs

Apache Software Foundation

SADAS s.r.l.

Initial release

2012

2018

2017

2015

2006

Current release

2.3, January 2021

Apache Ignite 2.6

8.0

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free trial version available

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

free trial 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

C++, Java, .Net

C++

Server operating systems

hosted

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

AIX
Linux
Windows

Data scheme

schema-free

Schema-free and OWL/RDFS-schema support

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

RESTful HTTP API

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
Python

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

by integration with AWS Lambda

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

none

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Kerberos/HDFS data loading

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency in MPP-Cluster

none

Immediate Consistency

Foreign keys

Referential integrity

not needed 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

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

managed by 'Learn by Usage'

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 and roles

Security Hooks for custom implementations

Access rights for users, groups and roles according to SQL-standard

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