DBMS > AlaSQL vs. Dgraph vs. MySQL vs. Transwarp KunDB vs. Vertica

System Properties Comparison AlaSQL vs. Dgraph vs. MySQL vs. Transwarp KunDB vs. Vertica

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Distributed and scalable native Graph DBMS

Widely used open source RDBMS

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Document store
Relational DBMS

Graph DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Column oriented

Secondary database models

Document store
Spatial DBMS

Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.04
Rank	#362	Overall
	#154	Relational DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

alasql.org

dgraph.io

www.mysql.com

www.transwarp.cn/en/product/kundb

www.vertica.com

Technical documentation

github.com/AlaSQL/alasql

dgraph.io/docs

dev.mysql.com/doc

vertica.com/documentation

Developer

Andrey Gershun & Mathias R. Wulff

Dgraph Labs, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Transwarp

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2014

2016

1995

2005

Current release

9.0.0, July 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C and C++

C++

Server operating systems

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

Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

with proprietary extensions

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JavaScript API

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

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

JavaScript

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication via Raft

Multi-source replication
Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

only for local storage and DOM-storage

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

Planned for future releases

Users with fine-grained authorization concept

no user groups or roles

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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