This paper investigates the use of algebraic estimators for numerical filtering and derivation applications. After giving some explanations for the choice of the estimator order, we focus on the order one. The frequency and time responses are compared with standard filtering and derivation methods, including the Kalman filter. These estimators are finally implemented and tested with real sensor signals. Results show that for quite equivalent performances, Kalman filter is less time consuming, while the first order algebraic filter is easier to implement without a priori knowledge on the signal.