DBMS > Amazon DynamoDB vs. Dgraph vs. Sqrrl vs. Transwarp Hippo vs. UniData,UniVerse

System Properties Comparison Amazon DynamoDB vs. Dgraph vs. Sqrrl vs. Transwarp Hippo vs. UniData,UniVerse

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

Adaptable, secure NoSQL built on Apache Accumulo

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Document store
Key-value store

Graph DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Vector DBMS

Multivalue 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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

aws.amazon.com/dynamodb

dgraph.io

sqrrl.com

www.transwarp.cn/en/subproduct/hippo

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.aws.amazon.com/dynamodb

dgraph.io/docs

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Amazon

Dgraph Labs, Inc.

Amazon

originally Sqrrl Data, Inc.

Rocket Software

Initial release

2012

2016

2012

2023

1985

Current release

1.0, May 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

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

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

optional

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

APIs and other access methods

RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

RESTful HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

Actionscript
C

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

C++
Java
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

making use of Hadoop

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

selectable replication factor

making use of Hadoop

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

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

Immediate Consistency

Foreign keys

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

Atomic updates per row, document, or graph entity

ACID

configurable

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

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

Role based access control and fine grained access rights

Access rights according to SQL-standard and operating system based

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