DBMS > AnzoGraph DB vs. Apache IoTDB vs. MarkLogic vs. Sequoiadb vs. SQL.JS

System Properties Comparison AnzoGraph DB vs. Apache IoTDB vs. MarkLogic vs. Sequoiadb vs. SQL.JS

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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Operational and transactional Enterprise NoSQL database

NewSQL database with distributed OLTP and SQL

Port of SQLite to JavaScript

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Document store
Relational DBMS

Relational DBMS

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	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

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

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

cambridgesemantics.com/anzograph

iotdb.apache.org

www.progress.com/marklogic

www.sequoiadb.com

sql.js.org

Technical documentation

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

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.progress.com/marklogic/documentation

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

sql.js.org/documentation/index.html

Developer

Cambridge Semantics

Apache Software Foundation

MarkLogic Corp.

Sequoiadb Ltd.

Alon Zakai

enhancements implemented by others

Initial release

2018

2001

2013

2012

Current release

2.3, January 2021

1.1.0, April 2023

11.0, December 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2.0

commercial

restricted free version is available

Open Source

Server: AGPL; Client: Apache V2

Open Source

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

Java

C++

JavaScript

Server operating systems

Linux

All OS with a Java VM (>= 1.8)

Linux
OS X
Windows

Linux

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

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

Schema can be enforced

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

SQL-like query language

yes

SQL92

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

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

JDBC
Native API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

proprietary protocol using JSON

JavaScript API

Supported programming languages

C++
Java
Python

C
C#
C++
Go
Java
Python
Scala

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

.Net
C++
Java
PHP
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

via XQuery or JavaScript

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Integration with Hadoop and Spark

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

can act as a resource manager in an XA/JTA transaction

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, with Range Indexes

yes

User concepts

Access control

Access rights for users and roles

yes

Role-based access control at the document and subdocument levels

simple password-based access control

More information provided by the system vendor

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Related products and services

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More resources

DB-Engines blog posts

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