DBMS > Amazon Aurora vs. InfluxDB vs. Solr vs. Vertica vs. YugabyteDB
System Properties Comparison Amazon Aurora vs. InfluxDB vs. Solr vs. Vertica vs. YugabyteDB
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| Name | Amazon Aurora Xexclude from comparison | InfluxDB Xexclude from comparison | Solr Xexclude from comparison | Vertica  OpenText™ Vertica™ Xexclude from comparison | YugabyteDB Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | MySQL and PostgreSQL compatible cloud service by Amazon | DBMS for storing time series, events and metrics | A widely used distributed, scalable search engine based on Apache Lucene | 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. | High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Relational DBMS | Time Series DBMS | Search engine | Relational DBMS Column oriented | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Document store | Spatial DBMS with GEO package | Spatial DBMS | Spatial DBMS Time Series DBMS | Document store Wide column store | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | aws.amazon.com/rds/aurora | www.influxdata.com/products/influxdb-overview | solr.apache.org | www.vertica.com | www.yugabyte.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html | docs.influxdata.com/influxdb | solr.apache.org/resources.html | vertica.com/documentation | docs.yugabyte.com github.com/yugabyte/yugabyte-db | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Amazon | Apache Software Foundation | OpenText previously Micro Focus and Hewlett Packard | Yugabyte Inc. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2015 | 2013 | 2006 | 2005 | 2017 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 2.7.6, April 2024 | 9.6.0, April 2024 | 12.0.3, January 2023 | 2.19, September 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | commercial | Open Source MIT-License; commercial enterprise version available | Open Source Apache Version 2 | commercial Limited community edition free | Open Source Apache 2.0 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | yes | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Implementation language | Go | Java | C++ | C and C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | hosted | Linux OS X through Homebrew | All OS with a Java VM runs as a servlet in servlet container (e.g. Tomcat, Jetty is included) | Linux | Linux OS X | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | yes | schema-free | yes Dynamic Fields enables on-the-fly addition of new fields | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | depending on used data model | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | yes | Numeric data and Strings | yes supports customizable data types and automatic typing | yes | 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 | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | yes | no | yes All search fields are automatically indexed | No Indexes Required. Different internal optimization strategy, but same functionality included. | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | yes | SQL-like query language | Solr Parallel SQL Interface | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | yes, PostgreSQL compatible | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | ADO.NET JDBC ODBC | HTTP API JSON over UDP | Java API RESTful HTTP/JSON API | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | JDBC YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | .Net Erlang Java JavaScript any language that supports sockets and either XML or JSON Perl PHP Python Ruby Scala | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | C C# C++ Go Java JavaScript (Node.js) PHP Python Ruby Rust Scala | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server-side scripts Stored procedures | yes | no | Java plugins | yes, PostgreSQL PL/pgSQL, with minor differences | yes sql, plpgsql, C | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | yes | no | yes User configurable commands triggered on index changes | yes, called Custom Alerts | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | horizontal partitioning | Sharding in enterprise version only | Sharding | horizontal partitioning, hierarchical partitioning | Hash and Range Sharding, row-level geo-partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | Source-replica replication | selectable replication factor in enterprise version only | yes | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | no | spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce | no Bi-directional Spark integration | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Eventual Consistency | Immediate Consistency | Strong consistency on writes and tunable consistency on reads | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | yes | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | no | optimistic locking | ACID | Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes based on RocksDB | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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 | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | fine grained access rights according to SQL-standard | simple rights management via user accounts | yes | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon Aurora | InfluxDB | Solr | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | 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 | YugabyteDB is an open source distributed SQL database for cloud native transactional... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | 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 | PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS.... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | Systems of record and engagement for cloud native applications that require resilience,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | 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 | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | 2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | 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 | Apache 2.0 license for the database » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Efficiency Unleashed: Streamlining Workflows with the InfluxDB Management API What is DevRel at InfluxData An Introductory Guide to Grafana Alerts What to Expect When You’re Expecting InfluxDB: A Guide Introduction to Apache Iceberg | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Amazon Aurora | InfluxDB | Solr | Vertica OpenText™ Vertica™ | YugabyteDB | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 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? | Elasticsearch replaced Solr as the most popular search engine Enterprise Search Engines almost double their popularity in the last 12 months The DB-Engines ranking includes now search engines | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | 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 | SOLR-led walkout demands better conditions for Compass workers (SOLR) Technical Data SOLR hosts teach-in of labor movements at Northwestern SOLR hosts May Day amid ongoing contract negotiations SearchStax Launches Serverless Solr Service to Accelerate Cloud-Native Application Development provided by Google News | Stonebraker Seeks to Invert the Computing Paradigm with DBOS How Embedded Analytics Help ISVs Overcome Challenges OpenText expands enterprise portfolio with AI and Micro Focus integrations Postgres pioneer Michael Stonebraker promises to upend the database once more OpenText integrates Micro Focus tech through Cloud Editions 23.3 provided by Google News | YugabyteDB Becomes First Distributed SQL Database Vendor to Complete CIS Benchmark Yugabyte Achieves PCI DSS Level 1 Compliance, Validating Secure and Scalable Distributed PostgreSQL for ... Yugabyte Named in the 2023 Gartner® Magic Quadrant™ for Cloud Database Management Systems The surprising link between Formula One and enterprise PostgreSQL optimisation Yugabyte Embraces 'No Downtime, No Limits,' as the Theme of the Upcoming Distributed SQL Summit Asia provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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