# Best Enterprise Time Series Databases *By [Bijou Barry](https://research.g2.com/insights/author/bijou-barry)* Products classified in the overall Time Series Databases category are similar in many regards and help companies of all sizes solve their business problems. However, enterprise business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Enterprise Business Time Series Databases to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Enterprise Business Time Series Databases category. In addition to qualifying for inclusion in the Time Series Databases category, to qualify for inclusion in the Enterprise Business Time Series Databases category, a product must have at least 10 reviews left by a reviewer from an enterprise business. ## How Many Time Series Databases Products Does G2 Track? **Total Products under this Category:** 52 ## How Does G2 Rank Time Series Databases Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 1,100+ Authentic Reviews - 52+ Products - Unbiased Rankings G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category. --- **Sponsored** ### QuestDB QuestDB is an open-source, SQL-first time-series database built for the most demanding workloads—from trading floors to mission control. A multi-tier design keeps hot data in native partitions and cold history in Parquet/object storage, queried via one SQL layer. Vectorized, columnar execution delivers high-throughput ingest and millisecond queries. Open formats (Parquet/Arrow) make it AI-ready and lock-in free. Deploy self-hosted or in your cloud (BYOC). [Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1761&secure%5Bdisplayable_resource_id%5D=1761&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1761&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=131714&secure%5Bresource_id%5D=1761&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Ftime-series-databases%2Fenterprise&secure%5Btoken%5D=90607bca27e70774d03744644500f91908e239744c0cb2e6f78fd21db7d6ebb1&secure%5Burl%5D=https%3A%2F%2Fquestdb.com&secure%5Burl_type%5D=company_website) --- ## What Are the Top-Rated Time Series Databases Products in 2026? ### 1. [KX](https://www.g2.com/products/kx-kx/reviews) We power the time-aware data-driven decisions that enable fast-moving organizations to realize the full potential of their AI investments and outpace competitors. Our technology delivers transformational value by addressing data challenges around completeness, timeliness, and efficiency. We enable organizations to understand change over time and generate faster, more accurate insights — at any scale, and with cost efficiency. Our technology is essential to the operations of the world's top investment banks, aerospace and defense, high-tech manufacturing, healthcare and life sciences, automotive, and fleet telematics organizations. The primary audience for KX encompasses line-of-business leaders, developers, data scientists, and data engineers who require sophisticated analytics capabilities to create high-performance, data-driven applications. With its unmatched speed and scalability, KX allows users to efficiently process large volumes of data, whether in cloud environments, on-premises, or at the edge. This flexibility ensures that organizations can integrate KX technology into their existing workflows seamlessly, enhancing their analytical capabilities without causing disruptions to ongoing operations. KX distinguishes itself in the analytics landscape through its independently benchmarked performance, recognized as the fastest available on the market. This speed is vital for businesses that depend on real-time data insights to inform their decision-making processes. By enabling users to uncover richer, actionable insights quickly, KX facilitates faster and more informed choices, driving competitive advantage and transformative growth. Its ability to manage complex data sets and deliver insights promptly is particularly advantageous for industries that operate in fast-paced environments, where timely information is critical. Key features of KX include advanced time series and vector data analytics capabilities, which enable efficient management and analysis of extensive data volumes. Furthermore, KX integrates seamlessly with popular analytics tools, enhancing their performance and allowing users to maximize their existing investments. The platform's architecture is designed for high performance, ensuring that organizations can scale their analytics operations as needed without sacrificing speed or efficiency. With a global presence across North America, Europe, and Asia Pacific, KX is trusted by leading organizations to spearhead their data and AI initiatives. By providing a powerful analytics solution, KX not only enhances operational efficiency but also fosters a culture of innovation, empowering businesses to remain competitive in an increasingly data-driven world. **Average Rating:** 4.6/5.0 **Total Reviews:** 50 **How Do G2 Users Rate KX?** - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 9.0/10) - **Ease of Admin:** 8.9/10 (Category avg: 8.3/10) - **Quality of Support:** 8.7/10 (Category avg: 8.8/10) **Who Is the Company Behind KX?** - **Seller:** [KX](https://www.g2.com/sellers/kx-a145756d-91d3-463e-a51d-9e13b1ac577c) - **Year Founded:** 1996 - **HQ Location:** NY, USA - **Twitter:** @kxsystems (4,169 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/kx-systems (527 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Financial Services, Banking - **Company Size:** 57% Enterprise, 25% Small-Business #### What Are KX's Pros and Cons? **Pros:** - Speed (11 reviews) - Performance (9 reviews) - Tool Power (7 reviews) - Efficiency (6 reviews) - Fast Processing (6 reviews) **Cons:** - Learning Curve (12 reviews) - Difficult Learning (7 reviews) - Steep Learning Curve (7 reviews) - Complexity (2 reviews) - Expensive (2 reviews) ### 2. [InfluxDB](https://www.g2.com/products/influxdata-influxdb/reviews) InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 300 open source Telegraf plugins, importing and monitoring data from any system is easy. InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data. Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge. To get started, InfluxData offers free training through InfluxDB University at https://university.influxdata.com **Average Rating:** 4.4/5.0 **Total Reviews:** 98 **How Do G2 Users Rate InfluxDB?** - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.0/10) - **Ease of Admin:** 8.7/10 (Category avg: 8.3/10) - **Quality of Support:** 8.6/10 (Category avg: 8.8/10) **Who Is the Company Behind InfluxDB?** - **Seller:** [InfluxData](https://www.g2.com/sellers/influxdata-c4358581-7be9-4eec-a0bc-bd083f9c5468) - **Year Founded:** 2012 - **HQ Location:** San Francisco, California - **Twitter:** @InfluxData (22 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/5159145/ (179 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer - **Top Industries:** Information Technology and Services, Computer Software - **Company Size:** 59% Small-Business, 23% Mid-Market ### 3. [Aerospike](https://www.g2.com/products/aerospike/reviews) The Aerospike Real-time Data Platform enables organizations to act instantly across billions of transactions while reducing server footprint by up to 80 percent. The Aerospike multi-cloud platform powers real-time applications with predictable sub-millisecond performance up to petabyte-scale with five-nines uptime with globally distributed, strongly consistent data. Applications built on the Aerospike Real-time Data Platform fight fraud, provide recommendations that dramatically increase shopping cart size, enable global digital payments, and deliver hyper-personalized user experiences to tens of millions of customers. Customers such as Airtel, Experian, Nielsen, PayPal, Snap, Wayfair, and Yahoo rely on Aerospike as their data foundation for the future. **Average Rating:** 4.4/5.0 **Total Reviews:** 80 **How Do G2 Users Rate Aerospike?** - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.0/10) - **Ease of Admin:** 8.3/10 (Category avg: 8.3/10) - **Quality of Support:** 8.9/10 (Category avg: 8.8/10) **Who Is the Company Behind Aerospike?** - **Seller:** [Aerospike](https://www.g2.com/sellers/aerospike) - **Year Founded:** 2009 - **HQ Location:** Mountain View, CA - **Twitter:** @aerospikedb (7,839 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/2696852/ (306 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Software Engineer - **Top Industries:** Marketing and Advertising, Information Technology and Services - **Company Size:** 45% Mid-Market, 34% Enterprise ### 4. [Druid](https://www.g2.com/products/druid/reviews) Apache Druid is an open source real-time analytics database. Druid combines ideas from OLAP/analytic databases, timeseries databases, and search systems to create a complete real-time analytics solution for real-time data. It includes stream and batch ingestion, column-oriented storage, time-optimized partitioning, native OLAP and search indexing, SQL and REST support, flexible schemas; all with true horizontal scalability on a shared nothing, cloud native architecture that makes it easy to deploy, monitor and manage at scale. It is downloadable for free for unlimited use from druid.apache.org and also hosted in the cloud by Imply Data. **Average Rating:** 4.3/5.0 **Total Reviews:** 28 **How Do G2 Users Rate Druid?** - **Has the product been a good partner in doing business?:** 7.7/10 (Category avg: 9.0/10) - **Ease of Admin:** 6.4/10 (Category avg: 8.3/10) - **Quality of Support:** 7.9/10 (Category avg: 8.8/10) **Who Is the Company Behind Druid?** - **Seller:** [Druid](https://www.g2.com/sellers/druid) - **Year Founded:** 1998 - **HQ Location:** Rio de Janeiro, Rio de Janeiro - **Twitter:** @druid (4 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/druid_2/ (77 employees on LinkedIn®) **Who Uses This Product?** - **Top Industries:** Computer Software - **Company Size:** 52% Enterprise, 29% Mid-Market ### 5. [Epsilon3](https://www.g2.com/products/epsilon3/reviews) Epsilon3 is the first AI-powered procedure and resource management tool designed for teams that engineer, build, test, and operate advanced products and systems. ✔ Standardize & Optimize Processes Our interoperable procedure execution system replaces inefficient checklists managed with paper, spreadsheets, docs, and outdated planning tools. Automatically track every step to ensure quality, consistency, and traceability. ✔ Fuel Rapid Iteration & Innovation Built-in version control, conditional workflows, and real-time data synchronization keep stakeholders on the same page. Enable continuous improvement and quick, data-driven decisions to stay far ahead of the competition. ✔ Streamline & Scale Operations Securely integrate siloed systems and automate repetitive, error-prone tasks to boost productivity and prevent delays. Simplify training, reduce costs, and maintain efficiency as your operations expand to meet demand. Epsilon3 is trusted by industry leaders like NASA, Blue Origin, Firefly Aerospace, Sierra Space, Redwire, Shift4, AeroVironment, Commonwealth Fusion Systems, and other commercial and government organizations. The company and platform were built by engineering leaders from SpaceX, NASA, and Google. Learn how: https://www.epsilon3.io/ **Average Rating:** 4.2/5.0 **Total Reviews:** 259 **How Do G2 Users Rate Epsilon3?** - **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.0/10) - **Ease of Admin:** 8.7/10 (Category avg: 8.3/10) - **Quality of Support:** 8.9/10 (Category avg: 8.8/10) **Who Is the Company Behind Epsilon3?** - **Seller:** [Epsilon3](https://www.g2.com/sellers/epsilon3) - **Company Website:** https://epsilon3.io - **Year Founded:** 2021 - **HQ Location:** Los Angeles, California - **Twitter:** @Epsilon3Inc (1,054 Twitter followers) - **LinkedIn® Page:** https://www.linkedin.com/company/epsilon3inc (32 employees on LinkedIn®) **Who Uses This Product?** - **Who Uses This:** Customer Service Representative - **Top Industries:** Aviation & Aerospace, Financial Services - **Company Size:** 43% Mid-Market, 40% Enterprise #### What Are Epsilon3's Pros and Cons? **Pros:** - Ease of Use (80 reviews) - Procedure Management (42 reviews) - Features (30 reviews) - Efficiency (27 reviews) - Efficiency Improvement (24 reviews) **Cons:** - Learning Curve (35 reviews) - Complexity (33 reviews) - Confusing Procedures (29 reviews) - Complex Procedures (27 reviews) - Confusion (24 reviews) ## What Is Time Series Databases? [Database Software](https://www.g2.com/categories/database-software) ## What Software Categories Are Similar to Time Series Databases? - [Relational Databases](https://www.g2.com/categories/relational-databases) - [Document Databases](https://www.g2.com/categories/document-databases) - [Database as a Service (DBaaS) Providers](https://www.g2.com/categories/database-as-a-service-dbaas) - [Time Series Intelligence Software](https://www.g2.com/categories/time-series-intelligence) - [Columnar Databases](https://www.g2.com/categories/columnar-databases) - [Vector Database Software](https://www.g2.com/categories/vector-database) - [Real-time Analytic Database Software](https://www.g2.com/categories/real-time-analytic-database) --- ## How Do You Choose the Right Time Series Databases? ### What You Should Know About Time Series Databases Software ### What are Time Series Databases Software? The growing number of different data types leads to the proliferation of different types of databases to facilitate its storage and analysis. Among the fast-growing data types is time series data—data which is timestamped and created over time—which is on the rise with the growth of the internet of things (IoT). Although it is frequently possible to store this data in other types of data stores, time series data has special properties—the data is append-only, making it worthwhile to consider a made-to-order database solution. The first challenge for selecting a database is finding the best structure for the data to be stored. In certain cases there is a natural fit—for example, airline flight information fits very well in a graph database as this mimics real-life patterns—while long-form web content usually slots into document databases. With time series databases software, users are able to store any data that has a timestamp, such as log data, sensor data, and industrial telemetry data. The use cases are manifold. For example, application developers use this software for the purpose of application monitoring to collect data points in real time and better understand application performance. In addition, IoT developers benefit from time series databases as they store and process sensor data, such as smart home devices, to determine how they are performing over time. Key Benefits of Time Series Databases Software - Provide scale and speed, with faster processing time than relational databases - Offer a tool which is specifically geared toward time series data - Allow for structured, organized data storage and management ### Why Use Time Series Databases Software? Like other databases, time series databases are primarily maintained by a database administrator or team. Owing to its wide range of coverage, time series databases are also accessible by several organizations within a company. Departments such as development, IT, billing, and others may also have access to time series databases, pending their assigned uses within the company. **Predict future —** Make informed predictions about future events, observe real-time changes, and capture historical anomalies. **Understand past —** Understand past data with a purpose-built database. ### Who Uses Time Series Databases Software? Time series databases software is highly flexible and is used by diverse teams throughout a company, making it particularly beneficial. For collecting extra large data sets in real time, big data processing and distribution systems are helpful. These tools are built to scale for businesses that are constantly collecting enormous amounts of data. Pulling data sets may be more challenging with big data processing and distribution systems, but the insights received is valuable due to the granularity of the data. **Database administrators —** Time series databases have grown in popularity since they are easier to implement, have greater flexibility, and tend to have faster data retrieval times. Database administrators use these tools to maintain and manage their time series data, ensuring it is properly stored. **Data scientists —** As data science, including artificial intelligence, is fueled by data, it is key that this data is stored in the most effective and efficient manner. This ensures that the data can be queried and analyzed properly. ### Kinds of Time Series Database Software Although all time series databases store timestamped data, they differ in the manner in which this data is stored, the relation between the various data points, and the method in which the data is queried. **Relational databases —** Relational databases are traditional database tools used to align information into rows and columns. The structure allows for easy querying using SQL. Relational databases are used to store both simple information, such as identities and contact information, and complex information critical to business operations. They are highly scalable and can be stored on-premises, in the cloud, or through hybrid systems. **NoSQL databases —** NoSQL databases such as graph databases are a great option for unstructured data. If the user needs to render a value that is easily found by its key, then a key-value store is the fastest and most scalable. The drawback is a much more limited querying ability, implying its limitations for analytic data. Conversely, rendering a user’s email address based on the username or caching web data is a simple and fast solution in a key-value store. ### Time Series Databases Software Features Time series databases, designed specifically for time series data, provide the user with the features they need to successfully store, process, and analyze this data. **Querying using time—** Time series databases allow users to query data using time, allowing them to search or analyze the data across a given time period, even by a fraction of a second. **Data security —** Time series database solutions include data security features to protect the data stored by a business in its databases. **Database creation and maintenance —** Time series databases software allows users to quickly create brand-new relational databases and modify them with ease. **Scalability —** Times series database solutions grow with the data and is hence scalable, with the only pain point being physical or cloud storage capacity. **Operating system (OS) compatibility —** Relational database solutions are compatible with numerous OS. **Recovery —** Whether a database needs to be rolled back or outrightly recovered, some time series database solutions offer recovery features in the event any errors occur. ### Trends Related to Time Series Databases Software **Databases and data aggregation —** Debate continues on the use of relational databases versus NoSQL databases, as data aggregation continues to rise among businesses. Organizations need to determine the best way to store their data as data-driven products and services require immense data backing. In reality, the two database types should be used together. While relational databases excel in structured data storage, NoSQL databases (non-relational databases) shine when there’s no real structure to how data should be collected and stored. Both relational and non-relational databases scale quite easily, given the right software supporting them. This shouldn’t be a "this versus that" debate, but a "this and that" collaboration. **Big data —** Data has become the backbone of conducting business in the information age. As data drives business decisions and trends, it’s important that the data be digestible, easy to follow, and easy to reference. That’s why big data software mostly falls back on relational database solutions. Designed with strict organization, referencing, and referral in mind, relational databases absorb and store massive amounts of data to be later digested in the decision-making process. ### Potential Issues with Time Series Databases Software **Unstructured data —** Time series databases struggle when handling unstructured data. Time series databases hinge on data being structured to properly create relationships between data points and data tables. If a company uses mostly unstructured data, they should consider a NoSQL database solution or data quality software to clean and structure unstructured data. **Query lag —** Time series databases store massive quantities of data, but with that advantage, such database tools run queries slowly on larger data sets. This is mainly due to the sheer volume of data being queried. In situations where queries might traverse significant quantities of data, they should be based on specific values whenever possible. Also, querying strings takes significantly longer than querying numerics, so focusing on the latter may help improve search times. ### Software and Services Related to Time Series Databases Software Finding the right database solution involves finding a tool that best fits a particular use case, including the type of data involved and the type of analysis that needs to be done with that data. The format of the data also determines the right database solution for a given company. **Time series intelligence software —** Users focusing on analyzing, as opposed to just storing time series data, may leverage [time series intelligence software](https://www.g2.com/categories/time-series-intelligence). By utilizing embedded machine learning, time series intelligence tools pull out previously hidden insights—such as microtrends and anomalies—without requiring a human to dig through the data manually, saving a business time and resources. **NoSQL databases —** While relational databases solutions excel with structured data, [NoSQL databases](https://www.g2.com/categories/nosql-databases) more effectively store loosely structured and unstructured data. NoSQL databases solutions pair well with [relational databases](https://www.g2.com/categories/relational-databases) if a company deals with diverse data that can be collected by both structured and unstructured means. **Relational databases —** [Relational databases](https://www.g2.com/categories/relational-databases) are helpful in creating scalable repositories for business information. They are also quality tools for back-end application support. They may be synced to applications to make data available to end users. **Data quality software —** Relational databases struggle with handling unstructured data, and duplicate or incorrect data may throw off the accuracy of results once data becomes structured. [Data quality software](https://www.g2.com/categories/data-quality) helps clean and structure data, which makes it easier to create a formal relational database for that data.