DBMS > AnzoGraph DB vs. HEAVY.AI vs. LokiJS vs. Microsoft SQL Server vs. SAP SQL Anywhere

System Properties Comparison AnzoGraph DB vs. HEAVY.AI vs. LokiJS vs. Microsoft SQL Server vs. SAP SQL Anywhere

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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial 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	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

cambridgesemantics.com/anzograph

github.com/heavyai/heavydb
www.heavy.ai

github.com/techfort/LokiJS

www.microsoft.com/en-us/sql-server

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

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

docs.heavy.ai

techfort.github.io/LokiJS

learn.microsoft.com/en-US/sql/sql-server

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Cambridge Semantics

HEAVY.AI, Inc.

Microsoft

SAP

formerly Sybase

Initial release

2018

2016

2014

1989

1992

Current release

2.3, January 2021

5.10, January 2022

SQL Server 2022, November 2022

17, July 2015

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2; enterprise edition available

Open Source

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

JavaScript

C++

Server operating systems

Linux

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

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

yes

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

via views

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

JDBC
ODBC
Thrift
Vega

JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C++
Java
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Server-side scripts

Stored procedures

user defined functions and aggregates

View functions in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

Round robin

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

none

yes, but depending on the SQL-Server Edition

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

fine grained access rights according to SQL-standard

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