In contrast to most other database systems, Berkeley DB provides relatively simple data access services.
Records in Berkeley DB are (key, value) pairs. Berkeley DB supports only a few logical operations on records. They are:
Notice that Berkeley DB never operates on the value part of a record. Values are simply payload, to be stored with keys and reliably delivered back to the application on demand.
Both keys and values can be arbitrary byte strings, either fixed-length or variable-length. As a result, programmers can put native programming language data structures into the database without converting them to a foreign record format first. Storage and retrieval are very simple, but the application needs to know what the structure of a key and a value is in advance. It cannot ask Berkeley DB, because Berkeley DB doesn't know.
This is an important feature of Berkeley DB, and one worth considering more carefully. On the one hand, Berkeley DB cannot provide the programmer with any information on the contents or structure of the values that it stores. The application must understand the keys and values that it uses. On the other hand, there is literally no limit to the data types that can be store in a Berkeley DB database. The application never needs to convert its own program data into the data types that Berkeley DB supports. Berkeley DB is able to operate on any data type the application uses, no matter how complex.
Because both keys and values can be up to four gigabytes in length, a single record can store images, audio streams, or other large data values. Large values are not treated specially in Berkeley DB. They are simply broken into page-sized chunks, and reassembled on demand when the application needs them. Unlike some other database systems, Berkeley DB offers no special support for binary large objects (BLOBs).
Berkeley DB is not a relational database.
First, Berkeley DB does not support SQL queries. All access to data is through the Berkeley DB API. Developers must learn a new set of interfaces in order to work with Berkeley DB. Although the interfaces are fairly simple, they are non-standard.
SQL support is a double-edged sword. One big advantage of relational databases is that they allow users to write simple declarative queries in a high-level language. The database system knows everything about the data and can carry out the command. This means that it's simple to search for data in new ways, and to ask new questions of the database. No programming is required.
On the other hand, if a programmer can predict in advance how an application will access data, then writing a low-level program to get and store records can be faster. It eliminates the overhead of query parsing, optimization, and execution. The programmer must understand the data representation, and must write the code to do the work, but once that's done, the application can be very fast.
Second, Berkeley DB has no notion of schema and data types in the way that relational systems do. Schema is the structure of records in tables, and the relationships among the tables in the database. For example, in a relational system the programmer can create a record from a fixed menu of data types. Because the record types are declared to the system, the relational engine can reach inside records and examine individual values in them. In addition, programmers can use SQL to declare relationships among tables, and to create indices on tables. Relational engines usually maintain these relationships and indices automatically.
In Berkeley DB, the key and value in a record are opaque to Berkeley DB. They may have a rich internal structure, but the library is unaware of it. As a result, Berkeley DB cannot decompose the value part of a record into its constituent parts, and cannot use those parts to find values of interest. Only the application, which knows the data structure, can do that. Berkeley DB does support indices on tables and automatically maintain those indices as their associated tables are modified.
Berkeley DB is not a relational system. Relational database systems are semantically rich and offer high-level database access. Compared to such systems, Berkeley DB is a high-performance, transactional library for record storage. It's possible to build a relational system on top of Berkeley DB. In fact, the popular MySQL relational system uses Berkeley DB for transaction-protected table management, and takes care of all the SQL parsing and execution. It uses Berkeley DB for the storage level, and provides the semantics and access tools.
Object-oriented databases are designed for very tight integration with object-oriented programming languages. Berkeley DB is written entirely in the C programming language. It includes language bindings for C++, Java, and other languages, but the library has no information about the objects created in any object-oriented application. Berkeley DB never makes method calls on any application object. It has no idea what methods are defined on user objects, and cannot see the public or private members of any instance. The key and value part of all records are opaque to Berkeley DB.
Berkeley DB cannot automatically page in objects as they are accessed, as some object-oriented databases do. The object-oriented application programmer must decide what records are required, and must fetch them by making method calls on Berkeley DB objects.
Berkeley DB does not support network-style navigation among records, as network databases do. Records in a Berkeley DB table may move around over time, as new records are added to the table and old ones are deleted. Berkeley DB is able to do fast searches for records based on keys, but there is no way to create a persistent physical pointer to a record. Applications can only refer to records by key, not by address.
Berkeley DB is not a standalone database server. It is a library, and runs in the address space of the application that uses it. If more than one application links in Berkeley DB, then all can use the same database at the same time; the library handles coordination among the applications, and guarantees that they do not interfere with one another.
Recent releases of Berkeley DB allow programmers to compile the library as a standalone process, and to use RPC stubs to connect to it and to carry out operations. However, there are some important limitations to this feature. The RPC stubs provide exactly the same API that the library itself does. There is no higher-level access provided by the standalone process. Tuning the standalone process is difficult, since Berkeley DB does no threading in the library (applications can be threaded, but the library never creates a thread on its own).
It is possible to build a server application that uses Berkeley DB for data management. For example, many commercial and open source Lightweight Directory Access Protocol (LDAP) servers use Berkeley DB for record storage. LDAP clients connect to these servers over the network. Individual servers make calls through the Berkeley DB API to find records and return them to clients. On its own, however, Berkeley DB is not a server.
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