DBMS > Apache Impala vs. Graph Engine vs. GraphDB vs. Redis vs. ScyllaDB

System Properties Comparison Apache Impala vs. Graph Engine vs. GraphDB vs. Redis vs. ScyllaDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

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.

Cassandra and DynamoDB compatible wide column store

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Graph DBMS
RDF store

Key-value store

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

Wide column store

Secondary database models

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Key-value store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

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

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Website

Technical documentation

impala.apache.org/impala-docs.html

www.graphengine.io/docs/manual

graphdb.ontotext.com/documentation

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

docs.scylladb.com

Social network pages

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Microsoft

Ontotext

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

ScyllaDB

Initial release

2013

2010

2000

2009

2015

Current release

4.1.0, June 2022

10.4, October 2023

7.2.5, May 2024

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

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

Open Source

Open Source (AGPL), commercial license available

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.

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

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

C++

.NET and C

Java

C++

Server operating systems

Linux

.NET

All OS with a Java VM
Linux
OS X
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

Data scheme

yes

schema-free and OWL/RDFS-schema support; RDF shapes

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

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.

Secondary indexes

yes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

with RediSearch module

yes

cluster global secondary indices

SQL

Support of SQL

SQL-like DML and DDL statements

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

with RediSQL module

SQL-like DML and DDL statements (CQL)

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

proprietary protocol

RESP - REdis Serialization Protocol

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

.Net
C#
Clojure
Java
JavaScript (Node.js)
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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

well-defined plugin interfaces; JavaScript server-side extensibility

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

yes, Lua

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

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

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Constraint checking

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts and optimistic locking

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

in-memory tables

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

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

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
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ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
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Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
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Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
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ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
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Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
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ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
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ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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News

Riding the Databricks Wave with Hybrid Knowledge Graphs
6 June 2024

Matching Skills and Candidates with Graph RAG
31 May 2024

A Triple Store RAG Retriever
29 May 2024

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.