GridDB vs InfluxDB

If you are choosing an open source time series database to run on your own infrastructure, GridDB and InfluxDB are two of the most established options — and in 2026 they make a surprisingly different bargain with you. GridDB is a purpose-built time series database whose free Community Edition can query and analyze your full data history. InfluxDB’s free, open source edition — InfluxDB 3 Core — is a modern, fast, single-node engine that InfluxData itself describes as a “recent-data engine,” with the production-grade historical and scaling capabilities reserved for its commercial tiers.

We build GridDB, so we’ll say it plainly: for self-hosted, open source time series workloads that need to retain and query history, we think GridDB Community Edition is the stronger choice. But InfluxDB 3 is an impressive piece of engineering, it has the larger ecosystem by far, and there are real workloads where Core is exactly right. This page lays out the differences honestly so you can decide for yourself.

A note on versions before we start: InfluxDB 1.x and 2.x are now in maintenance mode, and InfluxDB 3 is the current line. This comparison is primarily GridDB Community Edition vs InfluxDB 3 Core, since those are the two free, self-hosted, open source editions — an apples-to-apples match for the scope most people are actually deciding on.

At a Glance

Architecture: Purpose-Built vs Object-Storage Engine

Both databases are well-engineered; they optimize for different things.

GridDB was designed by Toshiba specifically for IoT telemetry. It is in-memory-first — memory is the primary store, disk is secondary — with an event-driven engine built to minimize per-operation overhead. In a clustered deployment (Enterprise Edition) data is distributed across nodes automatically; the open source Community Edition runs that engine on a single node. The design assumes high-frequency data from many devices, retained and queryable over time.

InfluxDB 3 is a ground-up rewrite (the engine formerly called InfluxDB IOx) built in Rust on a modern open-data foundation: Apache Arrow for in-memory columnar processing, Apache DataFusion for query execution, and Apache Parquet for columnar storage on object stores. Its headline architectural feature is being diskless — it persists to S3, GCS, or Azure Blob Storage, separating compute from storage. This is genuinely modern and has real advantages: cheap and effectively unlimited storage, stateless and portable nodes, and a hot-data cache that serves recent queries from memory without touching the object store.

The practical consequence cuts both ways. InfluxDB 3’s columnar-on-Parquet design is excellent for analytical scans and gives it the unlimited cardinality that the old TSM engine struggled with. GridDB’s in-memory-first, per-container layout favors high-frequency ingestion and per-device range scans, and — as the next sections cover — keeps the full dataset queryable on local disk without the recent-data caveats that constrain InfluxDB 3 Core.

Data Model: Key-Container vs Measurements

GridDB uses a Key-Container model. Each data source — typically each sensor or device — gets its own container, addressed by key. TimeSeries containers treat the timestamp as the row key and provide time-specific operations (sampling, interpolation, time-window aggregation) natively. This maps directly onto how IoT fleets are structured: many devices, each its own stream, each locatable without scanning structures shared with every other device.

InfluxDB organizes data into measurements containing tagged points (tags are indexed metadata; fields are the values). In v3 this is stored columnar, which is what enables fast analytical aggregation and unlimited tag cardinality. If you think in terms of metrics and dimensions, and you want SQL over them, this model is comfortable and powerful.

Which is better depends on access pattern: per-device reads/writes at high cardinality favor GridDB’s containers; broad analytical aggregation across all series favors InfluxDB’s columnar measurements.

Scalability: Both Free Editions Are Single-Node

It’s worth being precise here, because neither free edition scales out horizontally — and that’s true on both sides.

InfluxDB 3 Core is single-node, full stop. Clustering, multi-node deployment, high availability, and read replicas are all reserved for the commercial InfluxDB 3 Enterprise (or the Kubernetes-based InfluxDB Clustered) product. This is not new behavior: InfluxData removed clustering from the open source edition back in 2016 and has kept it commercial ever since. GridDB is the same on the open source side: Community Edition runs as a single node, and multi-node clustering, replication, and failover are part of the commercial GridDB Enterprise Edition (and GridDB Cloud).

So on clustering, it’s a wash — both put horizontal scale-out and HA behind a paid tier. If multi-node clustering on a free, open source edition is your hard requirement, neither fits.

But clustering is not where these two free editions actually diverge. The decisive difference is what a single node can do with your data over time — and that’s the next section.

The Recent-Data Limitation

This is the difference that matters most between the free editions, and the one most likely to surprise people coming from InfluxDB 1.x or 2.x.

InfluxData describes InfluxDB 3 Core as a “recent-data engine,” and that phrasing is deliberate. Core does not include a compactor — the background process that rewrites the many small Parquet files produced by ingestion into larger, sorted, indexed blocks. Without compaction, small files accumulate and query performance on older data degrades over time. The compactor is an Enterprise feature.

There is also a single-query time-span limit. Historically, Core capped both writes and queries to a 72-hour window. In early 2025 InfluxData relaxed this: you can now write data with any historical timestamp, and the restriction on what period you can query was lifted — but the span a single query can cover remains limited (rooted in a cap on how many Parquet files one query plan will scan), precisely because there is no compactor to consolidate them. The net effect, per InfluxData’s own positioning and third-party documentation, is that Core is suited to real-time monitoring of roughly the last few days of data and is not recommended for long-term storage and historical analysis. For that, you move to Enterprise.

This is where GridDB’s free edition has a decisive edge. GridDB Community Edition — on its single node — queries your full historical range with no comparable caveat, and includes built-in time series compression in the open source edition. Long-term retention and analysis are simply part of CE. So while neither free edition clusters, GridDB CE’s single node is a genuine long-term time series store, whereas InfluxDB 3 Core’s single node is, by design, a recent-data engine.

We want to be fair: if your actual use case is real-time dashboards and alerting over recent data on a single node — a very common pattern — Core handles it extremely well, with sub-10ms queries on hot data and a genuinely “run and go” setup. The limitation only bites when you need long-range history.

Licensing

This is where InfluxDB earns an honest point against us.

InfluxDB 3 Core’s license is more permissive than GridDB’s. Core is released under the MIT and Apache 2.0 licenses — classic, unrestricted open source with no copyleft obligations. You can do essentially anything with it.

GridDB Community Edition licenses the server under AGPL v3 (a strong copyleft license) and the client libraries under Apache 2.0. For the common case — running GridDB unmodified as the database behind your application, talking to it through the Apache 2.0 clients — AGPL imposes no obligations on your application code. The copyleft only triggers if you modify the GridDB server itself and offer that modified server as a network service. Organizations with blanket AGPL bans should note this; most others will find it a non-issue.

But license permissiveness is only one axis, and it’s worth being clear about what each free edition actually delivers. Both reserve multi-node clustering for a paid tier. The difference is in the single node: InfluxDB 3 Core is freely licensed but deliberately capability-limited for anything beyond recent data — no compaction, recent-data focus — so long-term historical analysis means buying Enterprise. GridDB CE’s single node is fully capable for long-term workloads — compression, full-range queries, and a dual NoSQL/SQL interface, all under the AGPL — without Core’s recent-data ceiling. So InfluxDB has the more permissive license; GridDB has the more capable free edition for historical work.

(For completeness: InfluxData offers a free Home license for InfluxDB 3 Enterprise for non-commercial at-home use, which unlocks the full feature set for hobbyists. It is not licensed for commercial self-hosting.)

Performance

GridDB’s in-memory-first design and per-container layout favor high-frequency ingestion and per-device range scans across the full dataset. InfluxDB 3’s columnar Parquet engine and DataFusion query layer favor analytical aggregation and high-cardinality scans of recent data, with object storage decoupling storage cost from compute. The Time Series Benchmark Suite (TSBS) supports both, and results vary enormously with cardinality, batch size, query mix, and — for InfluxDB Core specifically — how much historical data has accumulated without compaction. Run it against your own workload shape.

White Paper: Cloud_TSDB_Evaluation_GridDB_Influx_Mongo

White Paper: TimeSeries_Database_Benchmark_GridDB_InfluxDB

Ecosystem and Operations

InfluxDB wins on ecosystem. It is one of the most widely deployed time series databases in the world, with Telegraf as a best-in-class collection agent, broad SQL tooling compatibility, an enormous body of community content, integrations everywhere, and a built-in Python processing engine in v3 for in-database transformation and alerting.

GridDB’s ecosystem is smaller but covers the IoT stack well: official clients for Java, Python, C, Go, Node.js, and PHP; a Kafka Connector for streaming pipelines; a Grafana plugin; and integrations with Telegraf, Fluentd, and Logstash.

When to Choose Which

Choose GridDB if:

• Your workload is high-frequency, high-cardinality sensor/IoT ingestion
• You need to store and query long-term historical data on the free edition (InfluxDB Core can’t, without compaction)
• You want built-in compression and a purpose-built time series engine in the open source edition
• You value having both a fast NoSQL (TQL) path and SQL (JDBC) access to the same data

Choose InfluxDB 3 Core if:

• Your use case is real-time monitoring and alerting over recent data (roughly the last few days)
• A single node meets your needs and you don’t require built-in HA
• You want an object-storage-native, diskless deployment (S3/GCS/Azure Blob)
• You value the InfluxDB/Telegraf ecosystem and a modern columnar SQL engine, and the most permissive possible license

A note on scale for both: if you need clustering or high availability, that’s a paid step either way — GridDB Enterprise Edition on one side, InfluxDB 3 Enterprise on the other. Neither free edition clusters, so factor that into a long-term decision.

FAQ

Is InfluxDB open source?

Partially, and it depends on the edition. InfluxDB 3 Core is genuinely open source under MIT and Apache 2.0 — but it is single-node and optimized for recent data. The production capabilities (clustering, high availability, compaction for long-term data) are in InfluxDB 3 Enterprise and InfluxDB Clustered, which are commercial products. InfluxDB 1.x and 2.x are open source but now in maintenance mode.

Can free InfluxDB run as a cluster?

No. InfluxDB 3 Core is single-node only; clustering has been a commercial (Enterprise) feature since 2016.

Can free GridDB run as a cluster?

No. GridDB Community Edition is single-node. Multi-node clustering, replication, and failover are part of the commercial Enterprise Edition (and GridDB Cloud).

What is the InfluxDB 3 Core “72-hour limit”?

A design constraint stemming from Core’s lack of a compactor: a single query plan is limited in how many Parquet files (and therefore how wide a time range) it can scan. InfluxData lifted the original restrictions on writing and querying historical periods in early 2025, but the single-query-span limit remains, and query performance on aged data degrades without compaction. For long-range historical analysis, Enterprise (which includes the compactor) is the intended product.

Can GridDB query long-term historical data on the free edition?

Yes — GridDB Community Edition queries your full historical range on a single node, without the recent-data caveats that apply to InfluxDB 3 Core.

I’m still on InfluxDB 1.x or 2.x — does this apply?

Those versions are single-node open source on the older TSM engine (with the high-cardinality limitations v3 was built to fix), and they are now in maintenance. They could query full history, unlike Core’s single-query span limit. InfluxData’s recommended path is migration to v3. If you’re evaluating a move anyway, it’s a natural moment to compare against GridDB.

Which is faster?

It depends on workload shape. GridDB favors high-frequency ingestion and per-device queries across the full dataset; InfluxDB 3 favors analytical scans of recent, high-cardinality data on its columnar engine

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