DBMS > CrateDB vs. GridDB vs. InfluxDB vs. ScyllaDB vs. Sphinx
System Properties Comparison CrateDB vs. GridDB vs. InfluxDB vs. ScyllaDB vs. Sphinx
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Name | CrateDB Xexclude from comparison | GridDB Xexclude from comparison | InfluxDB Xexclude from comparison | ScyllaDB Xexclude from comparison | Sphinx Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Distributed Database based on Lucene | Scalable in-memory time series database optimized for IoT and Big Data | DBMS for storing time series, events and metrics | Cassandra and DynamoDB compatible wide column store | Open source search engine for searching in data from different sources, e.g. relational databases | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Spatial DBMS Search engine Time Series DBMS Vector DBMS | Time Series DBMS | Time Series DBMS | Wide column store | Search engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Relational DBMS | Key-value store Relational DBMS | Spatial DBMS with GEO package | Key-value store | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cratedb.com | griddb.net | www.influxdata.com/products/influxdb-overview | www.scylladb.com | sphinxsearch.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cratedb.com/docs | docs.griddb.net | docs.influxdata.com/influxdb | docs.scylladb.com | sphinxsearch.com/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Crate | Toshiba Corporation | ScyllaDB | Sphinx Technologies Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2013 | 2013 | 2013 | 2015 | 2001 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 5.1, August 2022 | 2.7.6, April 2024 | ScyllaDB Open Source 5.4.1, January 2024 | 3.5.1, February 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source | 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 Open Source (AGPL), commercial license available | Open Source GPL version 2, commercial licence available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform. | Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | C++ | Go | C++ | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support | Linux | Linux OS X through Homebrew | Linux | FreeBSD Linux NetBSD OS X Solaris Windows | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | Flexible Schema (defined schema, partial schema, schema free) | yes | schema-free | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes numerical, string, blob, geometry, boolean, timestamp | Numeric data and Strings | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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 | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | no | yes cluster global secondary indices | yes full-text index on all search fields | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | yes, but no triggers and constraints, and PostgreSQL compatibility | SQL92, SQL-like TQL (Toshiba Query Language) | SQL-like query language | SQL-like DML and DDL statements (CQL) | SQL-like query language (SphinxQL) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | ADO.NET JDBC ODBC PostgreSQL wire protocol Prometheus Remote Read/Write RESTful HTTP API | JDBC ODBC Proprietary protocol RESTful HTTP/JSON API | HTTP API JSON over UDP | Proprietary protocol (CQL) compatible with CQL (Cassandra Query Language, an SQL-like language) RESTful HTTP API (DynamoDB compatible) Thrift | Proprietary protocol | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | .NET Erlang Go community maintained client Java JavaScript (Node.js) community maintained client Perl community maintained client PHP Python R Ruby community maintained client Scala community maintained client | 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 | 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 | C++ unofficial client library Java Perl unofficial client library PHP Python Ruby unofficial client library | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | user defined functions (Javascript) | no | no | yes, Lua | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding | Sharding | Sharding in enterprise version only | Sharding | Sharding Partitioning is done manually, search queries against distributed index is supported | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Configurable replication on table/partition-level | Source-replica replication | selectable replication factor in enterprise version only | selectable replication factor Representation of geographical distribution of servers is possible | none | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no | Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Read-after-write consistency on record level | Immediate consistency within container, eventual consistency across containers | Eventual Consistency Tunable Consistency can be individually decided for each write operation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no unique row identifiers can be used for implementing an optimistic concurrency control strategy | ACID at container level | no | no Atomicity and isolation are supported for single operations | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes The original contents of fields are not stored in the Sphinx index. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | yes | yes Depending on used storage engine | yes in-memory tables | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | rights management via user accounts | Access rights for users can be defined per database | simple rights management via user accounts | Access rights for users can be defined per object | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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CrateDB | GridDB | InfluxDB | ScyllaDB | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | The enterprise database for time series, documents, and vectors. Distributed - Native... » more | 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 | ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling... » more | 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 | Highly-performant (efficiently utilizes full resources of a node and network; millions... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics... » more | Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system. » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | ScyllaDB is ideal for applications that require high throughput and low latency at... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Across all continents, CrateDB is used by companies of all sizes to meet the most... » more | 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 | Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®... » more | GitHub trending repository » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | See CrateDB pricing > » more | 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 | ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | A Detailed Guide to C# TimeSpan The Final Frontier: Using InfluxDB on the International Space Station Getting the Current Time in C#: A Guide Sync Data from InfluxDB v2 to v3 With the Quix Template Infrastructure Monitoring Basics: Getting Started with Telegraf, InfluxDB, and Grafana | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
CrateDB | GridDB | InfluxDB | ScyllaDB | Sphinx | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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? | The DB-Engines ranking includes now search engines CrateDB Partners with HiveMQ to Deliver a Seamless Data Management Architecture for IoT CrateDB Announces Availability of CrateDB on Google Cloud Marketplace CrateDB Appoints Sergey Gerasimenko as New CTO How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO 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 ... Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ... 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 Time-series database startup InfluxData debuts self-managed version of InfluxDB provided by Google News ScyllaDB on AWS is a NoSQL Database Built for Gigabyte-to-Petabyte Scale | Amazon Web Services Scylla Eyes Cassandra's NoSQL Workloads Scylla vs Cassandra: Performance Comparison - DataScienceCentral.com ScyllaDB Database Review | eWeek Scylla review: Apache Cassandra supercharged provided by Google News Switching From Sphinx to MkDocs Documentation — What Did I Gain and Lose Manticore is a Faster Alternative to Elasticsearch in C++ Perplexity AI: From Its Use To Operation, Everything You Need To Know About Googles Newest Challenger The Pirate Bay was recently down for over a week due to a DDoS attack How to Build 600+ Links in One Month provided by Google News |
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