DBMS > Apache Drill vs. GigaSpaces vs. Neo4j vs. Redis vs. Teradata

System Properties Comparison Apache Drill vs. GigaSpaces vs. Neo4j vs. Redis vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

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)

Primary database model

Document store
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Graph 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

Graph DBMS
Search engine

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	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

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

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

Technical documentation

drill.apache.org/docs

docs.gigaspaces.com/latest/landing.html

neo4j.com/docs

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

docs.teradata.com

Developer

Apache Software Foundation

Gigaspaces Technologies

Neo4j, Inc.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Teradata

Initial release

2012

2000

2007

2009

1984

Current release

1.20.3, January 2023

15.5, September 2020

5.19, April 2024

7.2.4, January 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPL version3, commercial licenses available

Open Source

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

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

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

Implementation language

Java, C++, .Net

Java, Scala

Server operating systems

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

hosted
Linux

Data scheme

schema-free

schema-free and schema-optional

schema-free

yes

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

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

yes

with RediSearch module

yes

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-99 for query and DML statements

with RediSQL module

yes

SQL 2016 + extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

proprietary protocol

RESP - REdis Serialization Protocol

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

Supported programming languages

C++

.Net
C++
Java
Python
Scala

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
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

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

Server-side scripts

Stored procedures

user defined functions

yes

User defined Procedures and Functions

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

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes, event driven architecture

yes

via event handler

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes using Neo4j Fabric

Sharding

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

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

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

Relationships in graphs

yes

Transaction concepts

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

ACID

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

Depending on the underlying data source

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.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

Role-based access control

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

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

More information provided by the system vendor

Specific characteristics

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Licensing and pricing models

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