DBMS > AnzoGraph DB vs. Microsoft SQL Server vs. Snowflake vs. Splunk vs. XTDB

System Properties Comparison AnzoGraph DB vs. Microsoft SQL Server vs. Snowflake vs. Splunk vs. XTDB

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

Microsofts flagship relational DBMS

Cloud-based data warehousing service for structured and semi-structured data

Analytics Platform for Big Data

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

cambridgesemantics.com/anzograph

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

www.snowflake.com

www.splunk.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

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

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

www.xtdb.com/docs

Developer

Cambridge Semantics

Microsoft

Snowflake Computing Inc.

Splunk Inc.

Juxt Ltd.

Initial release

2018

1989

2014

2003

2019

Current release

2.3, January 2021

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

commercial

free trial version available

commercial

restricted free version is available

commercial

Limited free edition and free developer edition available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Clojure

Server operating systems

Linux

Linux
Windows

hosted

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

yes

Splunk Search Processing Language for search commands

limited SQL, making use of Apache Calcite

APIs and other access methods

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

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

CLI Client
JDBC
ODBC

HTTP REST

HTTP REST
JDBC

Supported programming languages

C++
Java
Python

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

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

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

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

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

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes, but depending on the SQL-Server Edition

yes

Multi-source replication

yes, each node contains all data

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

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles

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