DBMS > GridGain vs. Oracle NoSQL vs. Redis vs. SAP HANA vs. Vertica

System Properties Comparison GridGain vs. Oracle NoSQL vs. Redis vs. SAP HANA vs. Vertica

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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.

In-memory, column based data store. Available as appliance or cloud service

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Key-value store
Relational DBMS

Document store
Key-value 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

Column oriented

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

with SAP Hana, Enterprise Edition
Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

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

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

www.gridgain.com

www.oracle.com/database/nosql/technologies/nosql

redis.com
redis.io

www.sap.com/products/hana.html

www.vertica.com

Technical documentation

www.gridgain.com/docs/index.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

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

help.sap.com/hana

vertica.com/documentation

Developer

GridGain Systems, Inc.

Oracle

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

SAP

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2007

2011

2009

2010

2005

Current release

GridGain 8.5.1

23.3, December 2023

7.2.5, May 2024

2.0 SPS07 (April 4, 2023), April 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

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

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

also available as a cloud based service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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++, .Net

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Appliance or cloud-service

Linux

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

optional

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like DML and DDL statements

with RediSQL module

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

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++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

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

SQLScript, R

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes (cache interceptors and events)

publish/subscribe channels provide some trigger functionality; RedisGears

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

through RedisGears

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

User concepts

Access control

Security Hooks for custom implementations

Access rights for users and roles

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

yes

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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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Licensing and pricing models

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