DBMS > AnzoGraph DB vs. InfluxDB vs. Kinetica vs. Microsoft SQL Server vs. NCache

System Properties Comparison AnzoGraph DB vs. InfluxDB vs. Kinetica vs. Microsoft SQL Server vs. NCache

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

DBMS for storing time series, events and metrics

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

Open-Source and Enterprise in-memory Key-Value Store

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Website

cambridgesemantics.com/anzograph

www.influxdata.com/products/influxdb-overview

www.kinetica.com

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

www.alachisoft.com/ncache

Technical documentation

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

docs.influxdata.com/influxdb

docs.kinetica.com

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

www.alachisoft.com/resources/docs

Developer

Cambridge Semantics

Kinetica

Microsoft

Alachisoft

Initial release

2018

2013

2012

1989

2005

Current release

2.3, January 2021

2.7.6, April 2024

7.1, August 2021

SQL Server 2022, November 2022

5.3.3, April 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

Open Source

Enterprise Edition available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

C#, .NET, .NET Core, Java

Server operating systems

Linux

Linux
OS X

through Homebrew

Linux

Linux
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL-like DML and DDL statements

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

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

HTTP API
JSON over UDP

JDBC
ODBC
RESTful HTTP API

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

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

C++
Java
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C++
Java
JavaScript (Node.js)
Python

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

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

support for stored procedures with SQL-Server CLR

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

in enterprise version only

Sharding

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

in enterprise version only

Source-replica replication

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

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 or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles

simple rights management via user accounts

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Market metrics

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Licensing and pricing models

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