DBMS > Alibaba Cloud MaxCompute vs. AnzoGraph DB vs. Hive vs. Microsoft Access vs. Redis

System Properties Comparison Alibaba Cloud MaxCompute vs. AnzoGraph DB vs. Hive vs. Microsoft Access vs. Redis

Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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.

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Graph DBMS
RDF store

Relational DBMS

Key-value store

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

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

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

Website

www.alibabacloud.com/product/maxcompute

cambridgesemantics.com/anzograph

hive.apache.org

www.microsoft.com/en-us/microsoft-365/access

redis.com
redis.io

Technical documentation

www.alibabacloud.com/help/en/maxcompute

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

cwiki.apache.org/confluence/display/Hive/Home

developer.microsoft.com/en-us/access

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

Developer

Alibaba

Cambridge Semantics

Apache Software Foundation

initially developed by Facebook

Microsoft

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2016

2018

2012

1992

2009

Current release

2.3, January 2021

3.1.3, April 2022

1902 (16.0.11328.20222), March 2019

7.2.4, January 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache Version 2

commercial

Bundled with Microsoft Office

Open Source

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

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.

Implementation language

Java

C++

Server operating systems

hosted

Linux

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

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

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.

Secondary indexes

yes

with RediSearch module

SQL

Support of SQL

SQL-like query language

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

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

with RediSQL module

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

JDBC
ODBC
Thrift

ADO.NET
DAO
ODBC
OLE DB

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Java

C++
Java
Python

C++
Java
PHP
Python

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions and aggregates

yes

user defined functions and integration of map-reduce

yes

since Access 2010 using the ACE-engine

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

Triggers

yes

since Access 2010 using the ACE-engine

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Automatic sharding

Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication in MPP-Cluster

selectable replication factor

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Kerberos/HDFS data loading

yes

query execution via MapReduce

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Eventual Consistency

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

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

but no files for transaction logging

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access rights for users, groups and roles

a simple user-level security was built in till version Access 2003

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

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