DBMS > Amazon DynamoDB vs. Drizzle vs. jBASE vs. Spark SQL vs. TigerGraph

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. jBASE vs. Spark SQL vs. TigerGraph

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A robust multi-value DBMS comprising development tools and middleware

Spark SQL is a component on top of 'Spark Core' for structured data processing

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Key-value store

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	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/dynamodb

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

spark.apache.org/sql

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/dynamodb

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

spark.apache.org/docs/latest/sql-programming-guide.html

docs.tigergraph.com

Developer

Amazon

Drizzle project, originally started by Brian Aker

Rocket Software (formerly Zumasys)

Apache Software Foundation

Initial release

2012

2008

1991

2014

2017

Current release

7.2.4, September 2012

5.7

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU GPL

commercial

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

C++

Scala

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

AIX
Linux
Windows

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

yes

with proprietary extensions

Embedded SQL for jBASE in BASIC

SQL-like DML and DDL statements

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

JDBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Java
PHP

.Net
Basic
Jabbascript
Java

Java
Python
R
Scala

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

none

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

Foreign keys

Referential integrity

yes

Relationships in graphs

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

User concepts

Access control

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights can be defined down to the item level

Role-based access control

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