DBMS > AnzoGraph DB vs. Dolt vs. Sequoiadb vs. Spark SQL vs. VoltDB

System Properties Comparison AnzoGraph DB vs. Dolt vs. Sequoiadb vs. Spark SQL vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

A MySQL compatible DBMS with Git-like versioning of data and schema

NewSQL database with distributed OLTP and SQL

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

cambridgesemantics.com/anzograph

github.com/dolthub/dolt
www.dolthub.com

www.sequoiadb.com

spark.apache.org/sql

www.voltdb.com

Technical documentation

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

docs.dolthub.com

www.sequoiadb.com/en/index.php?m=Files&a=index

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

docs.voltdb.com

Developer

Cambridge Semantics

DoltHub Inc

Sequoiadb Ltd.

Apache Software Foundation

VoltDB Inc.

Initial release

2018

2013

2014

2010

Current release

2.3, January 2021

3.5.0 ( 2.13), September 2023

11.3, April 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Scala

Java, C++

Server operating systems

Linux

Linux
macOS
Windows

Linux

Linux
OS X
Windows

Linux
OS X

for development

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

SQL-like query language

SQL-like DML and DDL statements

yes

only a subset of SQL 99

APIs and other access methods

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

CLI Client
HTTP REST

proprietary protocol using JSON

JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

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

.Net
C++
Java
PHP
Python

Java
Python
R
Scala

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

currently in alpha release

JavaScript

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Only one user is configurable, and must be specified in the config file at startup

simple password-based access control

Users and roles with access to stored procedures

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More resources

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