Digital transformation drives many businesses to produce bulks of information. Whether a small venture or a large organization, you need a reliable database to store and organize its essential data.
Databases are like the records room in physical offices. The information stored in these rooms is highly sensitive. Thus, it is crucial to be extra careful when accessing the said information.

Best Databases to Use in 2025

Many apps and databases are emerging left and right. Unfortunately, it can be challenging to determine which one will work best for you. So, here is a deep dive into the most popular databases in 2025.

#1: The Oracle

Oracle Database or Oracle is one of the most popular database management service systems. It features built-in assembly languages like Java, C, and C++.
This multi-model database system is produced and marketed by Oracle Corporation. Oracle is mainly used for running online transaction processing or OLTP, mixed database workloads, and data warehousing.

Key features:
· SQL and PL/SQL Support
· ResultSet Support
· Date-Time Data Types
· Two-Phase Commit Protocol
· Heterogeneous Replication
· Piecewise LONG Data Type

Companies Currently using Oracle Database
· Netflix
· eBay
· LinkedIn
· BackBase
· MIT
· Intuit
· Wealthsimple

#2: Redis

Redis was ranked as the Most Loved Database platform by Stack Overflow’s Annual Developer Survey. It is popular among developers due to its in-memory key-value database capabilities.
You can also use Redis as a distributed cache and message broker.

Key features:
· Data persistence
· Chat and messaging applications
· Gaming leaderboard applications
· Rich data structures
· High availability and scalability

Companies currently using Redis:
· Twitter
· GitHub
· Craigslist
· Snapchat

#3: Firebirdsql

Firebird is a database management system that is free to use. It is SQL relational and can operate on Microsoft Windows, Linux, macOS, and some Unix platforms.
This database is best for web applications that have upgraded multi-platform RDBMS. You have a variety of options when it comes to membership and commitments.

Key features:
· Common Table Expressions
· Highly compatible with NASI SQL
· Cross-database queries
· Flexible transactions management
· User-Defined Functions
· Active tables concept and events

#4: MySQL

When it comes to web application development, one of the rising databases in 2025 is MySQL. This database focuses on stability, maturity, and robustness.
MySQL uses structured query language and is written in C/C++. In addition, the most recent version of the database features an improved recovery option.

Key features:
· Scalable
· Client and utility programs
· Support for large databases
· Security
· Character sets

Companies that use MySQL:
· Uber
· Airbnb
· Amazon
· Pinterest
· Udemy
· Shopify

Interesting Read: What All it Takes to Build a Mobile App: A Detailed Mobile App Development Process Guide

#5: Elasticsearch

Elasticsearch is an open-search and analytics engine that is free to use. It can cater to all types of data like numerical, textural, structured, geospatial, and unstructured.
Shay Banon first introduced the search engine in 2010 as a full-text search engine that is distributed, multi-tenant capable and has a REST API.

Key features:
· Automatic node recovery
· Horizontal scalability
· Rack awareness
· Clustering and high availability
· Automatic data rebalancing
· Cross-datacenter replication
· Cross-cluster replication

Companies using Elasticsearch:
· Shopify
· Uber
· Slack
· Udemy
· Instacart
· LaunchDarkly
· CRED
· Robinhood

#6: Neo4j

Launched in 2007, Neo4j is an open-source, Java-based NoSQL database. It uses Cypher, a known query language and is known as one of the most efficient ways to describe relationship queries.
Neo4j saves your data in graphs, not tables. Its relationship system quickly allows you to make and use other relationships as shortcuts. This speeds up the domain data as the need arises.

Key features:
· Follows Property Graph Data Model
· Supports UNIQUE constraints
· Supports full ACID
· Supports Indexes by utilizing Apache Licence
· It contains a UI that executes CQL Commands

Companies using Neo4j
· AT&T
· Verizon
· Comcast
· Orange

#7: MS SQL Server

Microsoft also developed a tool to support database software, both for on-premise and cloud versions. MS SQL Server is Windows and Linux compatible and supports structured, semi-structured, and spatial data.
Although MS SQL Server is not as advanced as other databases on the list, it did undergo huge improvements over the years.

Key features:
· Intelligence across data
· Choice of language and platform
· End-to-end mobile BI
· Most secured database platform
· High-availability

Companies using MS SQL Server
· Accenture
· Microsoft
· Intuit
· doubleSlash
· Hepsiburada
· Alibaba Travels
· Stack Overflow

#8: Cassandra

Cassandra was developed in 2008 as a highly scalable database for an application. Today, it is known as an open core, distributed, comprehensive column store that is highly scalable. It is also one of various industries’ most widely used database management systems.

Key features:
· Supports replication
· Supports multi-datacenter replication
· Fault-tolerance
· MapReduce support
· Query language

Companies using Cassandra:
· Uber
· Netflix
· Facebook
· Instagram
· Reddit
· Spotify
· Accenture
· Instacart

#9: DynamoDB

DynamoDB is a database offered by Amazon on its web services portfolio. It is a proprietary NoSQL database service that is fully managed and supports document data structures and key-value.
The service that DynamoDB provides a similar data model to Dynamo but is different in implementation. In contrast to Dynamo’s multi-leader design, DynamoDB utilizes synchronous replications through several data centres.

Key features:
· Uses PartiQL
· Uses Amazon Kinesis Data Streams
· Resources DynamoDB tables at a faster rate
· Can export data from DynamoDB to Amazon Simple Storage Service

Companies that use DynamoDB:
· Zoom
· Dropbox
· The Pokemon Company International
· Capital One
· Samsung

#10: PostgreSQL

PostgreSQL is also known as Postgres. It is an open-source RDBMS or relational database management system. It is a free database that offers extensibility and compliance with SQL.
The system was named POSTGRES, paying tribute to its predecessor, the Ingres database. It was renamed in 1996 as a reflection of SQL support.

Key Features:
· Table inheritance
· User-defined types
· Foreign key referential integrity
· Sophisticated locking mechanism
· Vies, rules, subquery
· Nested transactions
· Asynchronous replication
· Multi-version concurrency control

Companies that use PostgreSQL
· Apple
· Instagram
· Skype
· Reddit
· IMDB
· Twitch
· International Space Station

#11: MariaDB

MariaDB is a MySQL Protocol and Clients compatible RDBMS or relational database management system. You can replace the MySQL server with Maria DB with no code changes.
This database features columns as storage with a highly parallel distributed data architecture. MariaDB is community-developed as open-source software under the GNU General Public License.

Key features:
· Wide selection of storage engines
· Uses standard and popular querying language
· Has InnoDB and XtraDB are known for high reliability and high performance
· Galera Cluster provides high up-time and prevents loss of data
· Has sequence engines that create various number sequences

Companies that use MariaDB:
· Deutsche Bank
· Nasdaq
· Verizon
· DBS Bank
· Red hat
· ServiceNow
· Walgreens

#12: SQLite

SQLite is an open-source library with an integrated RDBMS. It is one of the top databases developers use as it does not require configuration, a server, or installation.
SQLite has bindings to multiple programming languages. It follows PostgreSQL syntax. However, SQLite does not enforce type checking.

Key features:
· Available on UNIX and Windows
· Facilitates API for a variety of programming languages
· Cross-platform DBMS
· Facilitates efficient data storage
· Has variable column lengths for allocating only spaces for needed fields

Companies that use SQLite:
· Zendesk, Inc.
· Lorven Technologies
· CONFIDENTIAL RECORDS, INC.

#13: MongoDB

Developed by MongoDB, Inc, Mongo DB is a document-oriented database program classified as NoSQL. It uses JSON-like documents with optional schemas.
Before MongoDB, it was difficult to load and access data into RDBMS through object-oriented programming languages. In addition, they required extra application-level mapping. As a solution, MongoDB’s developers added Document Data.

Key features:
· Load balancing
· Replication for improved data availability/stability
· Ad-hoc queries for improved, real-time analytics
· More appropriate indexing for improved query executions
· Sharding

Companies that use MongoDB:
· eBay
· Shutterfly
· Bashar
· EA
· MetLife

#14: OrientDB

OrientDB is a Multi-model NoSQL database management system. It is open-source and written in Java.
OrientDB also supports graph, document, object, and key/value models.
The program supports various schema modes and has a strong profiling system for added security. OrientDB also uses multiple indexing processes based on Extendible hashing and B-tree.

Key features:
· Unmatched security
· 24×7 support
· Incremental backups
· Query profiler
· Metrics recording
· Distributed clustering configuration
· Live monitor with configurable alerts

Companies that use OrientDB:
· Securely
· Cove
· Velocorner
· GittiGidiyor
· Vagas.com
· Bright Powder

Interesting Read: Top 10 Best Web Development Technologies

#15: IBM DB2

Initially released by IBM in 1993, IBM DB2 is a collection of data management products that include database servers. They were intended to support the relational model but were eventually upgraded to support object-relational structures.
The brand name went through several changes until eventually settling to DB2. IBM offers DB2 LUW for Windows, Unix, and Linux. The most recent version of DB2 is the DB2 11.5, which features a faster query execution.

Key features:
· Scaling
· Multiple data types
· Multiple languages
· Continuous availability
· Automated administration and tuning

Companies that use IBM DB2
· Wells Fargo
· Audi AG
· Credit Suisse Group
· Huntington National Bank
· Penske

#16: Teradata

Teradata is a leading provider of cloud-based data warehousing and analytics solutions, known for its advanced capabilities in data management, analytics, and business intelligence. Teradata offers a variety of solutions that enable organizations to store, manage, and analyze large volumes of data, both structured and unstructured, in real-time.

Key features:
· Industry-Specific Solutions
· Teradata offers a hybrid cloud deployment model
· Provides a wide range of advanced analytics capabilities
· Offers a comprehensive set of data integration
· Offers a massively parallel processing

Companies that use Teradata
· Walmart
· Coca-Cola
· Verizon
· eBay

#17: Amazon Aurora

Amazon Aurora is a high-performance, scalable, and fully managed relational database service offered by Amazon Web Services (AWS). It is compatible with MySQL and PostgreSQL, providing users with the advantages of open-source databases and the reliability and scalability of AWS infrastructure.

Key features:
· Multi-Region Replication
· Automated Backups
· Point-in-Time Recovery
· It is highly scalable

Companies that use Amazon Aurora
· Netflix
· Airbnb
· Expedia
· Verizon

#18: Elastic Search

Elasticsearch is actually a a distributed search and analytics engine which is used as a partner database. It sits on top of your existing databases and indexes your data to make it searchable and analyzable in real-time. Think of it as a powerful search engine specifically designed for your own data, not the public web.

Key features:

· Full-text search
· Geospatial search
· Aggregations and analytics
· Scalability and elasticity
· RESTful API

Companies that use Elastic Search
· Uber
· GitHub
· The Washington Post

#19: Cockroach DB

CockroachDB is a resilient, distributed SQL database that allows businesses to scale globally without compromising data consistency. It’s ideal for cloud-native applications that require high availability and strong transactional integrity, making it popular among e-commerce and SaaS platforms.

Key features:

· Global Scalability
· Ensures consistency in distributed transactions.
· Automatically replicates data to recover from failures.
· Cloud-Native

Companies that use Cockroach DB
· DoorDash
· Bose
· Comcast

#20: Influx DB

InfluxDB is a leading time-series database designed for high-speed ingestion and real-time analytics. It’s commonly used in IoT, system monitoring, and financial analytics, where managing and analyzing time-stamped data is crucial.

Key features:

· Handles high-velocity data streams, perfect for IoT, DevOps, and real-time analytics.
· High Performance
· Edge and Cloud Support
· Includes tools for monitoring, alerting, and predictive analytics.

Companies that use Influx DB
· Tesla
· Siemens
· Cisco

Why Is There a Need for Reliable Databases in 2025?

Database reliability means that your database should be working flawlessly. Therefore, it should not cause you any problems as you entrust it with vital information about your organization.

• Having a reliable database is important because it:
• Ensures that your data is complete and accurate
• It is an essential foundation in building data trust
• Accomplishes data integrity initiatives
• Delivers trusted analytics and insights that can help in building better business strategies.
• It helps in improving the overall health of an organization’s data

Which emerging database should my company choose in 2025?

The choice of database depends on your specific use case:

• Graph Databases: Best for complex relationship data, such as social media networks or recommendation systems.
• Time-Series Databases: Ideal for monitoring real-time data, such as IoT sensor data, stock market analytics, or server monitoring.
• Distributed SQL Databases: Best for large-scale, cloud-native applications requiring strong consistency and horizontal scalability.
• Multi-Model Databases: Perfect if you need flexibility in managing different types of data models within a single database system.

What are the top databases for AI and machine learning in 2025?

The top databases optimized for AI and ML workloads in 2025 include Pinecone, Weaviate, Milvus, and ChromaDB, all of which are designed for handling high-dimensional vector data. Traditional databases like PostgreSQL with pgvector are also gaining traction due to their hybrid capabilities. These databases offer fast similarity search, real-time performance, and integrations with AI frameworks, making them ideal for applications like semantic search and generative AI.

FAQs on Latest Database To Use in 2025

Q1. Which databases are best for handling unstructured data in 2025?

A. In 2025, leading databases for unstructured data include MongoDB, Couchbase, and ArangoDB, which offer flexible document models and strong scalability. For AI-powered apps, vector databases like Qdrant and Chroma are emerging as powerful tools for indexing, querying, and analyzing unstructured embeddings generated by LLMs and neural networks.

Q2. What is the best vector database in 2025?

A. The top vector databases in 2025 are Pinecone, Weaviate, Milvus, and Qdrant , all purpose-built for storing and retrieving AI-generated vector embeddings. These databases are optimized for semantic search, recommendation engines, and LLM orchestration, and they integrate easily with frameworks like LangChain, Haystack, and OpenAI APIs.

Q3. Are traditional SQL databases still relevant in 2025?

A. Yes, traditional SQL databases like PostgreSQL, MySQL, and SQL Server remain widely used in 2025, especially when paired with extensions that support vector data or JSON. PostgreSQL, in particular, is evolving into a hybrid database platform with pgvector and TimescaleDB, making it highly relevant for AI, time-series, and analytics workloads.

Q4. What are the emerging trends in database technology for 2025?

A. Key database trends in 2025 include:

• Vector databases for AI/LLM applications
• Serverless and cloud-native databases like Neon and PlanetScale
• Multi-model databases that support relational, document, graph, and vector data
• Database-as-a-Service (DBaaS) adoption for scalability and zero-maintenance
• Real-time analytics engines like ClickHouse and Apache Pinot for streaming data