DBMS > Google Cloud Datastore vs. Ingres vs. Redis vs. Teradata vs. Trafodion

System Properties Comparison Google Cloud Datastore vs. Ingres vs. Redis vs. Teradata vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Well established 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.

A hybrid cloud data analytics software platform (Teradata Vantage)

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Relational DBMS

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

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

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

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

cloud.google.com/datastore

www.actian.com/databases/ingres

redis.com
redis.io

www.teradata.com

trafodion.apache.org

Technical documentation

cloud.google.com/datastore/docs

docs.actian.com/ingres

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

docs.teradata.com

trafodion.apache.org/documentation.html

Developer

Google

Actian Corporation

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Teradata

Apache Software Foundation, originally developed by HP

Initial release

2008

1974

originally developed at University Berkely in early 1970s

2009

1984

2014

Current release

11.2, May 2022

7.2.5, May 2024

Teradata Vantage 1.0 MU2, January 2019

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

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

commercial

Open Source

Apache 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.

Implementation language

C++, Java

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

hosted
Linux

Linux

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

with RediSearch module

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

SQL-like query language (GQL)

yes

with RediSQL module

yes

SQL 2016 + extensions

yes

APIs and other access methods

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

proprietary protocol

RESP - REdis Serialization Protocol

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

ADO.NET
JDBC
ODBC

Supported programming languages

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

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

using Google App Engine

yes

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

yes

UDFs, stored procedures, table functions in parallel

Java Stored Procedures

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

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

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

Sharding

Hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Ingres Replicator

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Multi-source replication
Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

through RedisGears

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Atomic execution of command blocks and scripts and optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

User concepts

Access control

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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