DBMS > AnzoGraph DB vs. NCache vs. Redis vs. Snowflake vs. Trino

System Properties Comparison AnzoGraph DB vs. NCache vs. Redis vs. Snowflake vs. Trino

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

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

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

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

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Graph DBMS
RDF store

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.alachisoft.com/ncache

redis.com
redis.io

www.snowflake.com

trino.io

Technical documentation

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

www.alachisoft.com/resources/docs

docs.redis.com/latest/index.html
redis.io/docs

docs.snowflake.net/manuals/index.html

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Cambridge Semantics

Alachisoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Snowflake Computing Inc.

Trino Software Foundation

Initial release

2018

2005

2009

2014

2012

2020 rebranded from PrestoSQL

Current release

2.3, January 2021

5.3.3, April 2024

7.2.5, May 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Enterprise Edition available

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C#, .NET, .NET Core, Java

Java

Server operating systems

Linux

Linux
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

hosted

Linux
macOS

for devlopment

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

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

yes

Typing

predefined data types such as float or date

partial

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

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

with RediSearch module

depending on connected data-source

SQL

Support of SQL

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

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

with RediSQL module

yes

APIs and other access methods

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

IDistributedCache
JCache
LINQ
Proprietary native API

proprietary protocol

RESP - REdis Serialization Protocol

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C++
Java
Python

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

support for stored procedures with SQL-Server CLR

Lua; Redis Functions coming in Redis 7 (slides and Github)

user defined functions

yes, depending on connected data-source

Triggers

yes

Notifications

publish/subscribe channels provide some trigger functionality; RedisGears

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

yes

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

yes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes, with selectable consistency level

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

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

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Immediate Consistency

depending on connected data-source

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

Atomic execution of command blocks and scripts and optimistic locking

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

depending on connected data-source

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

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

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

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

SQL standard access control

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

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