DBMS > Amazon Aurora vs. InfluxDB vs. Kdb vs. Oracle Berkeley DB vs. Redis
System Properties Comparison Amazon Aurora vs. InfluxDB vs. Kdb vs. Oracle Berkeley DB vs. Redis
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Name | Amazon Aurora Xexclude from comparison | InfluxDB Xexclude from comparison | Kdb Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | Redis Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | MySQL and PostgreSQL compatible cloud service by Amazon | DBMS for storing time series, events and metrics | High performance Time Series DBMS | Widely used in-process key-value store | 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. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Relational DBMS | Time Series DBMS | Time Series DBMS Vector DBMS | Key-value store supports sorted and unsorted key sets Native XML DBMS in the Oracle Berkeley DB XML version | Key-value store Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store | Spatial DBMS with GEO package | Relational DBMS | Document store with RedisJSON Graph DBMS with RedisGraph Spatial DBMS Search engine with RediSearch Time Series DBMS with RedisTimeSeries Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | aws.amazon.com/rds/aurora | www.influxdata.com/products/influxdb-overview | kx.com | www.oracle.com/database/technologies/related/berkeleydb.html | redis.com redis.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html | docs.influxdata.com/influxdb | code.kx.com | docs.oracle.com/cd/E17076_05/html/index.html | docs.redis.com/latest/index.html redis.io/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Amazon | Kx Systems, a division of First Derivatives plc | Oracle originally developed by Sleepycat, which was acquired by Oracle | Redis project core team, inspired by Salvatore Sanfilippo Development sponsored by Redis Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2015 | 2013 | 2000 kdb was released 2000, kdb+ in 2003 | 1994 | 2009 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 2.7.6, April 2024 | 3.6, May 2018 | 18.1.40, May 2020 | 7.2.4, January 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | commercial | Open Source MIT-License; commercial enterprise version available | commercial free 32-bit version | Open Source commercial license available | Open Source source-available extensions (modules), commercial licenses for Redis Enterprise | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | yes | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Go | q | C, Java, C++ (depending on the Berkeley DB edition) | C | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | hosted | Linux OS X through Homebrew | Linux OS X Solaris Windows | AIX Android FreeBSD iOS Linux OS X Solaris VxWorks Windows | BSD Linux OS X Windows ported and maintained by Microsoft Open Technologies, Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | yes | schema-free | yes | schema-free | schema-free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | Numeric data and Strings | yes | no | partial Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | no | yes | yes only with the Berkeley DB XML edition | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | yes table attribute 'grouped' | yes | yes with RediSearch module | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes | SQL-like query language | SQL-like query language (q) | yes SQL interfaced based on SQLite is available | with RediSQL module | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC | HTTP API JSON over UDP | HTTP API JDBC Jupyter Kafka ODBC WebSocket | proprietary protocol RESP - REdis Serialization Protocol | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | Ada C C# C++ D Delphi Eiffel Erlang Haskell Java JavaScript (Node.js) Objective-C OCaml Perl PHP Python Ruby Scheme Tcl | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | C C# C++ Go J Java JavaScript Lua MatLab Perl PHP Python R Scala | .Net Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET others Third-party libraries to manipulate Berkeley DB files are available for many languages C C# C++ Java JavaScript (Node.js) 3rd party binding Perl Python Tcl | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | user defined functions | no | Lua; Redis Functions coming in Redis 7 (slides and Github) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | yes with views | yes only for the SQL API | publish/subscribe channels provide some trigger functionality; RedisGears | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | Sharding in enterprise version only | horizontal partitioning | none | Sharding Automatic hash-based sharding with support for hash-tags for manual sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | selectable replication factor in enterprise version only | Source-replica replication | Source-replica replication | Multi-source replication with Redis Enterprise Pack Source-replica replication Chained replication is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no similar paradigm used for internal processing | no | through RedisGears | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate Consistency | Eventual Consistency Causal consistency can be enabled in Active-Active databases Strong consistency with Redis Raft Strong eventual consistency with Active-Active | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | no | ACID | Atomic execution of command blocks and scripts and optimistic locking | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes Data access is serialized by the server | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes Configurable mechanisms for persistency via snapshots and/or operations logs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | yes Depending on used storage engine | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | fine grained access rights according to SQL-standard | simple rights management via user accounts | rights management via user accounts | no | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Aurora | InfluxDB | Kdb | Oracle Berkeley DB | Redis | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | Integrated columnar database & programming system for streaming, real time and historical... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | provides seamless scalability; runs on industry standard server platforms; is top-ranked... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | tick database streaming sensor data massive intelligence applications oil and gas... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | kdb+ performance and reliability proven by our customers in critical infrastructure... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open source core with closed source clustering available either on-premise or on... » more | upon request » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | An Introductory Guide to Grafana Alerts What is DevRel at InfluxData What to Expect When You’re Expecting InfluxDB: A Guide Introduction to Apache Iceberg Converting Timestamp to Date in Java | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | Navicat for Redis: the award-winning Redis management tool with an intuitive and powerful graphical interface. » more CData: Connect to Big Data & NoSQL through standard Drivers. » more Redisson PRO: The ultra-fast Redis Java Client. » more Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Amazon Aurora | InfluxDB | Kdb | Oracle Berkeley DB | Redis | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cloud-based DBMS's popularity grows at high rates The popularity of cloud-based DBMSs has increased tenfold in four years Amazon - the rising star in the DBMS market | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | PostgreSQL is the DBMS of the Year 2018 MySQL, PostgreSQL and Redis are the winners of the March ranking MongoDB is the DBMS of the year, defending the title from last year Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ... Join the preview of Amazon Aurora Limitless Database | Amazon Web Services Build generative AI applications with Amazon Aurora and Knowledge Bases for Amazon Bedrock | Amazon Web Services Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ... New – Amazon Aurora Optimized Reads for Aurora PostgreSQL with up to 8x query latency improvement for I/O ... provided by Google News Introducing Amazon Timestream for InfluxDB: A managed service for the popular open source time-series database ... Amazon Timestream: Managed InfluxDB for Time Series Data InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services provided by Google News Turbocharging the Engine: KX Unleashes AI-First Transformation with kdb+ McLaren Applied and KX partner to enhance ATLAS software analytics capabilities Introducing Amazon FinSpace with Managed kdb Insights, a fully managed analytics engine, commonly used by capital ... KX ANNOUNCES KDB INSIGHTS AS FULLY MANAGED SERVICE ON AMAZON FINSPACE KX Brings the Power and Performance of kdb+ to Python Developers with PyKX provided by Google News ACM recognizes far-reaching technical achievements with special awards Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag The importance of bitcoin nodes and how to start one The stable version of AlmaLinux 9.0 has already been released provided by Google News General availability: Azure Cache for Redis triggers and bindings for Azure Functions | Azure updates Open Source Exodus: Redis Leads the Charge in Profit-Driven License Switch Boosting throughput for cloud databases Redis acquires storage engine startup Speedb to enhance its open-source database Redis expands data management capabilities with Speedb acquisition – Blocks and Files provided by Google News |
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