JPA Pitfalls: Generating IDs

JPA Pitfalls: Generating IDs

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October 24th, 2022

In this article we are going to discuss different JPA strategies for generating IDs. This article is part of the JPA Pitfalls series:

- JPA Pitfalls: Eager/Lazy Fetching

- JPA Pitfalls: Relationship Mapping

JPA makes it really easy to do things the wrong way, and makes it really unintuitive to do things right. In this blog post series I will go over some common JPA pitfalls, and introduce generating IDs.


JPA specification requires all entities to have an ID. ID is defined by annotating a field with @Id or @EmbeddedId annotations.

By default, ID must be assigned manually when inserting a new record. This is usually fine when an entity has a natural identifier. For example, all published books are assigned an ISBN, so if we were to make a book repository, we could use that as an ID and assign it manually to each book. It is important to note however that ID should be a compact data type, as it can have negative memory and performance implications otherwise, so we should be careful about using complex natural IDs.

For everything else, our JPA provider can automatically generate surrogate IDs for us when inserting new entities. To do this, we have to add a @GeneratedValue annotation:



private Long id;

As usual, JPA is trying to abstract all of the complex logic from us, so we don't have to worry about implementation details. Unfortunately, if we don't care about implementation details we can end up with a less performant implementation. This is something that is commonly known as a "leaky abstraction", and JPA is full of it.

In reality, there are many different ways to generate IDs, and we have to understand all of them in order to choose the best one depending on the circumstances. ID generation strategies that JPA providers support are:

  • GenerationType.SEQUENCE
  • GenerationType.IDENTITY
  • GenerationType.TABLE
  • GenerationType.AUTO

In order to specify our preferred strategy, we can pass the GenerationType as a strategy attribute of @GeneratedValue annotation. For example:


@GeneratedValue(strategy = GenerationType.IDENTITY)

private Long id;

In the following sections, we are going to go down the rabbit hole, see what these different strategies imply, and see which one you should prefer. If you don't care about the details, and just want a sensible default that is the best for most use-cases, you can skip to the Conclusion directly.

Sequence strategy

This strategy uses database sequences under the hood. A database sequence is a special user-defined object that yields a sequence of integers.

In Postgres, you can create a sequence with the following syntax:

create sequence _name_ start with _x_ increment by _y_


  • _name_ is a unique name of the sequence
  • _x_ is an initial value produced by the sequence, specified as an integer
  • _y_ is an integer value added to the current sequence value to create the next value

After a sequence is created, we can use the functions nextval, currval, and setval to operate on that sequence. For example, in order to get the next value in the sequence:

select nextval('sequence_name');

So now that we understand what a database sequence is, let's get back to JPA. Assuming that Hibernate is our JPA provider of choice, and we use the GenerationType.SEQUENCE strategy, Hibernate will by default use a sequence named hibernate_sequence. And if we use auto-ddl-generation feature of JPA, it will also create that sequence for us like this:

create sequence hibernate_sequence start with 1 increment by 1;

The default behavior above is not ideal for two reasons:

  • Hibernate uses a single sequence to generate IDs for all tables

This is bad for concurrency. Additionally, it is possible to run out of values eventually, because a sequence is internally stored as a fixed size integer.

  • Hibernate creates a sequence that is incremented only by 1

This disables the Hibernate's sequence ID pool generation optimization, which has negative performance implications. For each insert, hibernate will have to generate an additional select query in order to fetch the next ID from the sequence.

We can override the bad default by creating a custom sequence manually:

create sequence user_id_seq start with 1 increment by 50;

We can then tell Hibernate to use that custom sequence instead:


@GeneratedValue(strategy = GenerationType.SEQUENCE, generator = "user_id_seq")

private Long id;

This is better because:

  • We can use a different sequence for each table
  • We can define a sequence that generates values in increments of 50, which enables Hibernate's ID pool. Hibernate will now run a single select query to fetch the next sequence value, and will then increment the values internally for the next 50 insert statements. Once Hibernate runs out of IDs in the pool, it will then fetch the next sequence value from the database. This way, we significantly reduce the number of select statements that have to be sent, which improves performance dramatically.

Identity strategy

Relational databases support special types that are automatically incremented upon insertion. In Postgres, we can use smallserial, serial or bigserial:

create table t (id bigserial primary key);

These types are not compliant with the SQL standard, because Postgres added support for them before the standard introduced auto-incremented types. However, they are now standardized and you can use the following syntax instead:

create table t (id bigint primary key generated always as identity);

In Postgres, serial types are nothing special -- they are just syntax sugar and use the sequence type under the hood. So the above definition is equivalent to specifying:

create sequence t_id_seq;

create table t (id bigint not null default nextval('t_id_seq'));

alter sequence t_id_seq owned by;

In order to use serial types with JPA, we can specify that we want to use identity strategy:


@GeneratedValue(strategy = GenerationType.IDENTITY)

private Long id;

Hibernate can now create insert statements without specifying the ID column explicitly, and the ID will be automatically generated by the database.

"Nice!" -- you might say. That seems much better than creating sequences manually and then having to fetch sequence values with additional queries before inserting. Unfortunately, there is a catch. Turns out, this is not nice at all when used with JPA.

JPA provider needs to be aware of the generated ID because we might later want to do an update on the newly saved entity. So, even though it created a single insert statement, and our database generated the ID automatically, the JPA provider still needs to fetch that ID afterwards in order to know what the generated value is. This means that it would effectively have to execute this:

insert into t (c1, c2, c3) values (?, ?, ?);

select currval('t_id_seq');

In reality, this can be made slightly more efficient, because modern databases support the following statement:

insert into t (c1, c2, c3) values (?, ?, ?) returning *;

Where the returning clause causes insert to return inserted values similarly to the subsequent select statement. This is better because we reduced the number of necessary queries, but there is still one major problem -- using identity strategy disables JPA batch insert execution. With batch inserts, it is not possible to reliably associate generated IDs with the JPA entities afterwards, so JPA providers opt to disable batch inserts altogether when using identity strategy.

Table strategy

This strategy uses a separate table that emulates a sequence. When an application needs an ID, the JPA provider locks the table row, updates the stored value, and returns it to the application. This strategy has the worst performance compared to the previously discussed strategies and should be avoided if possible. It should be used only if the underlying database does not support sequences. Since most popular databases support sequences, I am not going to get into the details about this strategy, but you can read about it in the official Hibernate documentation if you would like to learn more.

Auto strategy

GenerationType.AUTO is the default strategy used by the JPA provider, so we don't have to specify it explicitly if we want to use it.

JPA specification does not state what the auto strategy actually is, so it is left to the JPA provider to decide which of the above strategies to use. If Hibernate is our JPA provider of choice, then it will try to use the sequence strategy if possible, but if the sequence is not supported by the underlying database, it will fallback to the table strategy.

Hibernate UUID Generator

So far we discussed only database generated IDs. It is also possible to generate IDs on the client side (in our application) using UUIDs.

UUID value is a very large 128bit number, so the probability of collision is extremely low, and it can be considered unique for all practical purposes. Because of these characteristics, we can have multiple instances of our app, all generating UUIDs independently without having to call the common database. UUIDs as such are great for distributed systems.

JPA specification does not support defining custom generators, but Hibernate itself has an extension that allows us to do that via the org.hibernate.annotations.GenericGenerator. On top of that, Hibernate also provides an implementation for UUID generator, so we don't have to write it ourselves.

We can use the Hibernate provided UUID generator like this:


@GeneratedValue(generator = "uuid2")

@GenericGenerator(name = "uuid2", strategy = "uuid2")

private UUID id;

Or even better, since Hibernate is able to inspect the type of our field, and is able to infer that we want to use the UUID generator when the field is of type java.lang.UUID, we can just write it like this instead:



private UUID id;

Using UUIDs has many benefits:

  • We don't need to query the database to get the next value
  • Since UUIDs are generated by Hibernate, it is aware of them and is able to use JPA batch insert execution

On the other side, UUID is not without its drawbacks:

  • Some relational databases (notably MySQL), by default, store data clustered by the primary key. This means that inserts have to be ordered in order to avoid a page miss upon insertion. But UUIDs are random by nature, so they will always cause a page miss, which is extremely bad for performance.
  • UUIDs are 128bit, which is double the size of a bigint, or four times the size of an integer. Since databases create a B-tree index for the primary key, this can cause the index to get bloated and less likely to fit into memory which would cause more frequent memory swapping which is bad for performance.


As we have seen, ID generation is a very complex topic and there is much to consider when choosing the best generation strategy for our particular use-case.

To summarize, here is a cheat sheet for choosing the best strategy (from worst to best):

  • Never use GenerationType.TABLE or GenerationType.AUTO because they are bad for performance while not providing any useful benefits
  • Using UUIDs for the primary key sounds amazing in theory, but it can have serious performance problems because of the way databases are implemented internally, so UUIDs should generally be avoided
  • GenerationType.IDENTITY disables JPA batch insert execution, so it does not have the optimal performance. However, it may be fine if you are not doing lots of inserts, so it can be considered for simplicity reasons
  • GenerationType.SEQUENCE enables JPA batch execution, but Hibernate has terrible defaults when creating a database sequence, so it should be avoided if not configured correctly
  • If you care about having the best performance, then you should use GenerationType.SEQUENCE, but create a custom sequence per table with the proper configuration. A sequence with an increment of 50 can be a good starting point, but it depends on how frequent your app is doing inserts, so it should be tweaked as needed

About the author

Bojan Stipic is a Software Engineer with over three years of experience working at our engineering hub in Novi Sad.

Bojan is interested in Full-stack web development, systems programming, programming language design, and compiler development. As for specific technologies, he feels most comfortable using technologies such as Java and React.

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