DBMS > eXtremeDB vs. Interbase vs. Redis vs. RRDtool vs. Vertica

System Properties Comparison eXtremeDB vs. Interbase vs. Redis vs. RRDtool vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

Light-weight proven RDBMS

originally from Borland

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.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

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

Time Series DBMS

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

Spatial DBMS
Time Series DBMS

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

Score	0.80
Rank	#214	Overall
	#99	Relational DBMS
	#18	Time Series DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

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

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

www.mcobject.com

www.embarcadero.com/products/interbase

redis.com
redis.io

oss.oetiker.ch/rrdtool

www.vertica.com

Technical documentation

www.mcobject.com/docs/extremedb.htm

docs.embarcadero.com/products/interbase

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

oss.oetiker.ch/rrdtool/doc

vertica.com/documentation

Developer

McObject

Embarcadero

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Tobias Oetiker

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2001

1984

2009

1999

2005

Current release

8.2, 2021

InterBase 2020, December 2019

7.2.5, May 2024

1.8.0, 2022

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

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

Open Source

GPL V2 and FLOSS

commercial

Limited community edition free

Cloud-based only

Only available as a cloud 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

C and C++

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

Android
iOS
Linux
OS X
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

HP-UX
Linux

Linux

Data scheme

yes

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

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

Numeric data only

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.

support of XML interfaces available

export as XML data possible

Exporting into and restoring from XML files possible

Secondary indexes

yes

with RediSearch module

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

SQL

Support of SQL

yes

with the option: eXtremeSQL

yes

with RediSQL module

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

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC

proprietary protocol

RESP - REdis Serialization Protocol

in-process shared library
Pipes

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

character-based, interactive, front-end utility

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

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

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

by defining events

yes

publish/subscribe channels provide some trigger functionality; RedisGears

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

none

Sharding

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

none

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

Interbase Change Views

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

none

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

through RedisGears

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

none

Immediate Consistency

Foreign keys

Referential integrity

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

Optimistic (MVCC) and pessimistic (locking) strategies available

yes

Multiversion concurreny control

yes

Data access is serialized by the server

yes

by using the rrdcached daemon

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

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; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
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Cost-based models and subscription-based models are both available. One license is...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.