DBMS > GigaSpaces vs. GridDB vs. InfluxDB vs. Redis vs. Vertica
System Properties Comparison GigaSpaces vs. GridDB vs. InfluxDB vs. Redis vs. Vertica
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Name | GigaSpaces Xexclude from comparison | GridDB Xexclude from comparison | InfluxDB Xexclude from comparison | Redis Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions | Scalable in-memory time series database optimized for IoT and Big Data | DBMS for storing time series, events and metrics | 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. | 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 | Document store Object oriented DBMS Values are user defined objects | Time Series DBMS | Time Series 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 | Graph DBMS Search engine | Key-value store Relational DBMS | Spatial DBMS with GEO package | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | www.gigaspaces.com | griddb.net | www.influxdata.com/products/influxdb-overview | redis.com redis.io | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.gigaspaces.com/latest/landing.html | docs.griddb.net | docs.influxdata.com/influxdb | docs.redis.com/latest/index.html redis.io/docs | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Gigaspaces Technologies | Toshiba Corporation | Redis project core team, inspired by Salvatore Sanfilippo Development sponsored by Redis Inc. | OpenText previously Micro Focus and Hewlett Packard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2000 | 2013 | 2013 | 2009 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 15.5, September 2020 | 5.1, August 2022 | 2.7.6, April 2024 | 7.2.5, May 2024 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2; Commercial licenses available | Open Source AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available | Open Source MIT-License; commercial enterprise version available | 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 | no | no | no | no | no 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 | C++ | Go | C | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux macOS Solaris Windows | Linux | Linux OS X through Homebrew | BSD Linux OS X Windows ported and maintained by Microsoft Open Technologies, Inc. | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | schema-free | schema-free | 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 | yes numerical, string, blob, geometry, boolean, timestamp | Numeric data and Strings | 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. | no XML can be used for describing objects metadata | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | no | yes with RediSearch module | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-99 for query and DML statements | SQL92, SQL-like TQL (Toshiba Query Language) | SQL-like query language | with RediSQL module | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | GigaSpaces LRMI Hibernate JCache JDBC JPA ODBC RESTful HTTP API Spring Data | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | HTTP API JSON over UDP | proprietary protocol RESP - REdis Serialization Protocol | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .Net C++ Java Python Scala | C C++ Go Java JavaScript (Node.js) Perl PHP Python Ruby | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust 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++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | yes | no | no | Lua; Redis Functions coming in Redis 7 (slides and Github) | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes, event driven architecture | yes | no | publish/subscribe channels provide some trigger functionality; RedisGears | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding in enterprise version only | Sharding Automatic hash-based sharding with support for hash-tags for manual sharding | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Multi-source replication synchronous or asynchronous Source-replica replication synchronous or asynchronous | Source-replica replication | selectable replication factor in enterprise version only | Multi-source replication with Redis Enterprise Pack Source-replica replication Chained replication is supported | 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 Map-Reduce pattern can be built with XAP task executors | Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs | no | through RedisGears | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency Consistency level configurable: ALL, QUORUM, ANY | Immediate consistency within container, eventual consistency across containers | 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 | no | no | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID at container level | no | Atomic execution of command blocks and scripts and optimistic locking | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes Data access is serialized by the server | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | 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 | yes | yes Depending on used storage engine | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Role-based access control | Access rights for users can be defined per database | simple rights management via user accounts | 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 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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GigaSpaces | GridDB | InfluxDB | Redis | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | GridDB is a highly scalable, in-memory time series database optimized for IoT and... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | 1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system. » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | GitHub trending repository » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Open Source license (AGPL v3 & Apache v2) Commercial license (subscription) » more | Open source core with closed source clustering available either on-premise or on... » more | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Monitoring Your Cloud Environments and Applications with InfluxDB Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS Using Parquet’s Bloom Filters Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API What is DevRel at InfluxData | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | CData: Connect to Big Data & NoSQL through standard Drivers. » more Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs. » more Navicat for Redis: the award-winning Redis management tool with an intuitive and powerful graphical interface. » more Redisson PRO: The ultra-fast Redis Java Client. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GigaSpaces | GridDB | InfluxDB | Redis | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | 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 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | GigaSpaces to hand out almost $14 million in dividends following Cloudify’s acquisition by Dell Data Sciences Corporation partners with GigaSpaces Technologies to usher DIH technology to enterprises in SA GigaSpaces Announces Version 16.0 with Breakthrough Data Integration Tools to Ease Enterprises' Digital ... GigaSpaces Spins Off Cloudify, Its Open Source Cloud Orchestration Unit Your occasional storage digest with GigaSpaces, Virtana and NAND ship data – Blocks and Files provided by Google News | General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ... Toshiba launches cloudy managed IoT database service running its own GridDB GridDB Use case Large-scale high-speed processing of smart meter data following the deregulation of electrical power ... General Availability of GridDB 5.1 Enterprise Edition ~ Continuous database usage in the event of data center failure ... IoT: Opt for the Right Open Source Database provided by Google News | Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services 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 AWS and InfluxData partner to offer managed time series database Timestream for InfluxDB provided by Google News | Redis acquires storage engine startup Speedb to enhance its open-source database Redis expands data management capabilities with Speedb acquisition – Blocks and Files Redis moves to source-available licenses In-memory database Redis wants to dabble in disk Redis switches licenses, acquires Speedb to go beyond its core in-memory database provided by Google News | OCI Object Storage Completes Technical Validation of Vertica in Eon Mode Stonebraker Seeks to Invert the Computing Paradigm with DBOS MapR Hadoop Upgrade Runs HP Vertica How Embedded Analytics Help ISVs Overcome Challenges OpenText expands enterprise portfolio with AI and Micro Focus integrations provided by Google News |
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