DBMS > Alibaba Cloud Table Store vs. Google Cloud Datastore vs. Oracle vs. Redis vs. Yaacomo

System Properties Comparison Alibaba Cloud Table Store vs. Google Cloud Datastore vs. Oracle vs. Redis vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Widely used RDBMS

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.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Website

www.alibabacloud.com/product/table-store

cloud.google.com/datastore

www.oracle.com/database

redis.com
redis.io

yaacomo.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

cloud.google.com/datastore/docs

docs.oracle.com/en/database

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

Developer

Alibaba

Google

Oracle

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Q2WEB GmbH

Initial release

2016

2008

1980

2009

Current release

23c, September 2023

7.2.5, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

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

commercial

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

C and C++

Server operating systems

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Android
Linux
Windows

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

yes

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

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

with proprietary extensions

with RediSQL module

yes

APIs and other access methods

HTTP API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

Supported programming languages

Java
Python

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

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

using Google App Engine

PL/SQL

also stored procedures in Java possible

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

Triggers

Callbacks using the Google Apps Engine

yes

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Sharding, horizontal partitioning

Sharding

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication using Paxos

Multi-source replication
Source-replica replication

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

can be realized in PL/SQL

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

Atomic single-row operations

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

isolation level can be parameterized

Atomic execution of command blocks and scripts and optimistic locking

ACID

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

In-memory capabilities

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

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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