DBMS > ArangoDB vs. Faircom EDGE vs. Google Cloud Bigtable vs. InfluxDB vs. SingleStore
System Properties Comparison ArangoDB vs. Faircom EDGE vs. Google Cloud Bigtable vs. InfluxDB vs. SingleStore
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Name | ArangoDB Xexclude from comparison | Faircom EDGE formerly c-treeEDGE Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | InfluxDB Xexclude from comparison | SingleStore former name was MemSQL Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Native multi-model DBMS for graph, document, key/value and search. All in one engine and accessible with one query language. | FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | DBMS for storing time series, events and metrics | MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Document store Graph DBMS Key-value store Search engine | Key-value store Relational DBMS | Key-value store Wide column store | Time Series DBMS | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Spatial DBMS with GEO package | Document store Spatial DBMS Time Series DBMS Vector DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | arangodb.com | www.faircom.com/products/faircom-edge | cloud.google.com/bigtable | www.influxdata.com/products/influxdb-overview | www.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | docs.arangodb.com | docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html | cloud.google.com/bigtable/docs | docs.influxdata.com/influxdb | docs.singlestore.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Developer | ArangoDB Inc. | FairCom Corporation | SingleStore Inc. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2012 | 1979 | 2015 | 2013 | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 3.11.5, November 2023 | V3, October 2020 | 2.7.6, April 2024 | 8.5, January 2024 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache Version 2; Commercial license (Enterprise) available | commercial Restricted, free version available | commercial | Open Source MIT-License; commercial enterprise version available | commercial free developer edition available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | no | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | ArangoDB Cloud –The Managed Cloud Service of ArangoDB. Provides fully managed, and monitored cluster deployments of any size, with enterprise-grade security. Get started for free and continue for as little as $0,21/hour. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | C++ | ANSI C, C++ | Go | C++, Go | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | Android Linux ARM, x86 Raspbian Windows | hosted | Linux OS X through Homebrew | Linux 64 bit version required | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free automatically recognizes schema within a collection | Flexible Schema (defined schema, partial schema, schema free) | schema-free | schema-free | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes string, double, boolean, list, hash | yes, ANSI Standard SQL Types | no | Numeric data and Strings | 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. | yes | no | no | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | yes | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | yes ANSI SQL queries | no | SQL-like query language | yes but no triggers and foreign keys | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | AQL Foxx Framework Graph API (Gremlin) GraphQL query language HTTP API Java & SpringData JSON style queries VelocyPack/VelocyStream | ADO.NET Direct SQL IoT Microservice layer JDBC MQTT (Message Queue Telemetry Transport) ODBC RESTful HTTP API | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | HTTP API JSON over UDP | Cluster Management API as HTTP Rest and CLI HTTP API JDBC MongoDB API ODBC | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Clojure Elixir Go Java JavaScript (Node.js) PHP Python R Rust | C C# C++ Java JavaScript PHP Python VB.Net | C# C++ Go Java JavaScript (Node.js) Python | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | Bash C C# Java JavaScript (Node.js) Python | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | JavaScript | yes .Net, JavaScript, C/C++ | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | yes | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding since version 2.0 | File partitioning Customizable business rules for partitioning | Sharding | Sharding in enterprise version only | Sharding hash partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication with configurable replication factor | yes Synchronous and asynchronous realtime replication based on transaction logs | Internal replication in Colossus, and regional replication between two clusters in different zones | selectable replication factor in enterprise version only | Source-replica replication stores two copies of each physical data partition on two separate nodes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | no can be done with stored procedures in JavaScript | no | yes | no | no can define user-defined aggregate functions for map-reduce-style calculations | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency configurable per collection or per write Immediate Consistency OneShard (highly available, fault-tolerant deployment mode with ACID semantics) | Immediate Consistency Tunable Consistency | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Immediate Consistency | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | yes relationships in graphs | yes when using SQL | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | ACID | Atomic single-row operations | no | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes across SQL and NoSQL | yes | yes | yes, multi-version concurrency control (MVCC) | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes | no | yes Depending on used storage engine | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | yes | Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL. | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | simple rights management via user accounts | Fine grained access control via users, groups and roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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ArangoDB | Faircom EDGE formerly c-treeEDGE | Google Cloud Bigtable | InfluxDB | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Graph and Beyond. With more than 11,000 stargazers on GitHub, ArangoDB is the leading... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Consolidation: As a native multi-model database, can be used as a full blown document... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Native multi-model in ArangoDB is being used for a broad range of projects across... » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Cisco, Barclays, Refinitive, Siemens Mentor, Kabbage, Liaison, Douglas, MakeMyTrip,... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | ArangoDB is the leading native multi-model database with over 11,000 stargazers on... » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Very permissive Apache 2 License for Community Edition & commercial licenses are... » more | Open source core with closed source clustering available either on-premise or on... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | Deploying InfluxDB and Telegraf to Monitor Kubernetes Telegraf 1.32 Release Notes An Introductory Guide to Cloud Security for IIoT Building Real-Time Android Apps with InfluxDB Cloud: Data Logging, Querying, and Visualization How to Use InfluxDB for Real-Time SpringBoot Application Monitoring | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
ArangoDB | Faircom EDGE formerly c-treeEDGE | Google Cloud Bigtable | InfluxDB | SingleStore former name was MemSQL | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | The Weight of Relational Databases: Time for Multi-Model? | 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? | Turbocharge Your Application Development Using WebAssembly With SingleStoreDB Cloud-Based Analytics With SingleStoreDB SingleStore: The Increasing Momentum of Multi-Model Database Systems ArangoDB Announces Release of ArangoDB 3.11 for Search, Graph and Analytics ArangoDB raises $10 million for NoSQL database management Graph, machine learning, hype, and beyond: ArangoDB open source multi-model database releases version 3.7 Here's the pitch deck a German software startup used to raise $10 million to move to San Francisco and take on Oracle ArangoDB 3.5 update improves multi-model database platform provided by Google News Data Technology Company FairCom Expands The Edge with 2 New Releases of its Edge Computing Products Brokers, Protocols, Platform Move Manufacturing Data Winners of the 2021 IoT Evolution Product of the Year Awards Announced How To Collect, Store, and Query IoT Data With MQTT + SQL Trend-Setting Products in Data and Information Management for 2023 provided by Google News Google Cloud adds graph processing to Spanner, SQL support to Bigtable Google introduces Bigtable SQL access and Spanner's new AI-ready features Google's AI-First Strategy Brings Vector Support To Cloud Databases Google expands BigQuery with Gemini, brings vector support to cloud databases Google Cloud Adds GenAI, Core Enhancements Across Data Platform provided by Google News InfluxData's Latest Updates Optimize Time Series Data for Better Performance, Scale and Management Run and manage open source InfluxDB databases with Amazon Timestream InfluxData avoids ’AI magic beans’ in InfluxDB time series database update for enterprises InfluxData Enhances InfluxDB 3.0 with Performance Upgrades and Self-Managed Option InfluxData makes performance, storage improvements to InfluxDB 3.0 provided by Google News SingleStore Partners With Snowflake to Help Users Build Faster, More Efficient Real Time AI Applications Achieve near real-time analytics on Amazon DynamoDB with SingleStore Third time was the charm for SingleStore in the cloud, CEO says SingleStore CEO sees little future for purpose-built vector databases Building a Modern Database: Nikita Shamgunov on Postgres and Beyond provided by Google News |
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